{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T16:44:56Z","timestamp":1778604296213,"version":"3.51.4"},"reference-count":137,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T00:00:00Z","timestamp":1740355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T00:00:00Z","timestamp":1740355200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-07021-3","type":"journal-article","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T16:24:16Z","timestamp":1740414256000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["An extensive bibliometric analysis of artificial intelligence techniques from 2013 to 2023"],"prefix":"10.1007","volume":"81","author":[{"given":"Aditi","family":"Bajpai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sonal","family":"Yadav","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naresh Kumar","family":"Nagwani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,24]]},"reference":[{"key":"7021_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2022.100514","volume":"19","author":"SS Gill","year":"2022","unstructured":"Gill SS, Xu M, Ottaviani C, Patros P, Bahsoon R, Shaghaghi A, Uhlig S (2022) AI for next generation computing: emerging trends and future directions. Internet Things 19:100514","journal-title":"Internet Things"},{"issue":"9","key":"7021_CR2","doi-asserted-by":"publisher","first-page":"12973","DOI":"10.1007\/s11042-022-12208-4","volume":"81","author":"H Gao","year":"2022","unstructured":"Gao H, Ding X (2022) The research landscape on the artificial intelligence: a bibliometric analysis of recent 20 years. Multimed Tools Appl 81(9):12973\u201313001","journal-title":"Multimed Tools Appl"},{"issue":"1\u20132","key":"7021_CR3","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/S0004-3702(01)00129-1","volume":"134","author":"M Campbell","year":"2002","unstructured":"Campbell M, Hoane AJ Jr, Hsu FH (2002) Deep blue. Artif Intell 134(1\u20132):57\u201383","journal-title":"Artif Intell"},{"key":"7021_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/8812542","volume":"2021","author":"X Zhai","year":"2021","unstructured":"Zhai X, Chu X, Chai CS, Jong MSY, Istenic A, Spector M, Li Y (2021) A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity 2021:1\u201318","journal-title":"Complexity"},{"issue":"3","key":"7021_CR5","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/s43681-021-00043-6","volume":"1","author":"A Van Wynsberghe","year":"2021","unstructured":"Van Wynsberghe A (2021) Sustainable AI: AI for sustainability and the sustainability of AI. AI Ethics 1(3):213\u2013218","journal-title":"AI Ethics"},{"key":"7021_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118221","volume":"209","author":"Z Shao","year":"2022","unstructured":"Shao Z, Zhao R, Yuan S, Ding M, Wang Y (2022) Tracing the evolution of AI in the past decade and forecasting the emerging trends. Expert Syst Appl 209:118221","journal-title":"Expert Syst Appl"},{"key":"7021_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2019.08.002","volume":"57","author":"YK Dwivedi","year":"2021","unstructured":"Dwivedi YK, Hughes L, Ismagilova E, Aarts G, Coombs C, Crick T, Williams MD (2021) Artificial intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int J Inf Manag 57:101994","journal-title":"Int J Inf Manag"},{"key":"7021_CR8","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1016\/j.rser.2017.04.018","volume":"77","author":"SK Jha","year":"2017","unstructured":"Jha SK, Bilalovic J, Jha A, Patel N, Zhang H (2017) Renewable energy: present research and future scope of artificial intelligence. Renew Sustain Energy Rev 77:297\u2013317","journal-title":"Renew Sustain Energy Rev"},{"issue":"2","key":"7021_CR9","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1016\/j.rser.2008.01.006","volume":"13","author":"A Mellit","year":"2009","unstructured":"Mellit A, Kalogirou SA, Hontoria L, Shaari S (2009) Artificial intelligence techniques for sizing photovoltaic systems: a review. Renew Sustain Energy Rev 13(2):406\u2013419","journal-title":"Renew Sustain Energy Rev"},{"issue":"3","key":"7021_CR10","doi-asserted-by":"publisher","first-page":"277","DOI":"10.5853\/jos.2017.02054","volume":"19","author":"EJ Lee","year":"2017","unstructured":"Lee EJ, Kim YH, Kim N, Kang DW (2017) Deep into the brain: artificial intelligence in stroke imaging. J Stroke 19(3):277","journal-title":"J Stroke"},{"issue":"11","key":"7021_CR11","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.1070\/RCR4746","volume":"86","author":"II Baskin","year":"2017","unstructured":"Baskin II, Madzhidov TI, Antipin IS, Varnek AA (2017) Artificial intelligence in synthetic chemistry: achievements and prospects. Russ Chem Rev 86(11):1127","journal-title":"Russ Chem Rev"},{"key":"7021_CR12","volume":"3","author":"M Wakchaure","year":"2023","unstructured":"Wakchaure M, Patle BK, Mahindrakar AK (2023) Application of AI techniques and robotics in agriculture: a review. Artif Intell Life Sci 3:100057","journal-title":"Artif Intell Life Sci"},{"key":"7021_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2021.102528","volume":"61","author":"S Chinchanachokchai","year":"2021","unstructured":"Chinchanachokchai S, Thontirawong P, Chinchanachokchai P (2021) A tale of two recommender systems: the moderating role of consumer expertise on artificial intelligence based product recommendations. J Retail Consum Serv 61:102528","journal-title":"J Retail Consum Serv"},{"key":"7021_CR14","doi-asserted-by":"crossref","unstructured":"Io HN, Lee CB (2019) Understanding the adoption of chatbot: a case study of Siri. In: Advances in Information and Communication Networks: Proceedings of the 2018 Future of Information and Communication Conference (FICC), vol 1. Springer, pp 632\u2013643","DOI":"10.1007\/978-3-030-03402-3_44"},{"issue":"3","key":"7021_CR15","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1148\/radiol.2019190613","volume":"291","author":"CP Langlotz","year":"2019","unstructured":"Langlotz CP, Allen B, Erickson BJ, Kalpathy-Cramer J, Bigelow K, Cook TS, Kandarpa K (2019) A roadmap for foundational research on artificial intelligence in medical imaging: from the 2018 NIH\/RSNA\/ACR\/The academy workshop. Radiology 291(3):781\u2013791","journal-title":"Radiology"},{"issue":"2128","key":"7021_CR16","doi-asserted-by":"publisher","first-page":"20170357","DOI":"10.1098\/rsta.2017.0357","volume":"376","author":"SJ Mikhaylov","year":"2018","unstructured":"Mikhaylov SJ, Esteve M, Campion A (2018) Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration. Philos Trans R Soc A Math Phys Eng Sci 376(2128):20170357","journal-title":"Philos Trans R Soc A Math Phys Eng Sci"},{"key":"7021_CR17","doi-asserted-by":"crossref","unstructured":"Majid I, Lakshmi YV (2022) An analysis of artificial intelligence initiatives and programmes in India. In: Convergence of Deep Learning and Artificial Intelligence in Internet of Things. CRC Press, pp 281\u2013292","DOI":"10.1201\/9781003355960-19"},{"key":"7021_CR18","first-page":"19","volume-title":"Concepts of artificial intelligence and its application in modern healthcare systems","author":"B Singh","year":"2024","unstructured":"Singh B, Singh M, Devi R (2024) Artificial intelligence in medical imaging for developing countries: challenges and opportunities. Concepts of artificial intelligence and its application in modern healthcare systems. CRC Press, Boca Raton, pp 19\u201341"},{"issue":"6","key":"7021_CR19","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1038\/s42256-020-0183-4","volume":"2","author":"F Wu","year":"2020","unstructured":"Wu F, Lu C, Zhu M, Chen H, Zhu J, Yu K, Pan Y (2020) Towards a new generation of artificial intelligence in China. Nat Mach Intell 2(6):312\u2013316","journal-title":"Nat Mach Intell"},{"issue":"1","key":"7021_CR20","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s10798-023-09812-2","volume":"34","author":"W Park","year":"2024","unstructured":"Park W, Kwon H (2024) Implementing artificial intelligence education for middle school technology education in Republic of Korea. Int J Technol Des Educ 34(1):109\u2013135","journal-title":"Int J Technol Des Educ"},{"key":"7021_CR21","doi-asserted-by":"publisher","first-page":"34403","DOI":"10.1109\/ACCESS.2018.2819688","volume":"6","author":"J Liu","year":"2018","unstructured":"Liu J, Kong X, Xia F, Bai X, Wang L, Qing Q, Lee I (2018) Artificial intelligence in the 21st century. IEEE Access 6:34403\u201334421","journal-title":"IEEE Access"},{"key":"7021_CR22","doi-asserted-by":"publisher","first-page":"1545","DOI":"10.1007\/s00542-019-04426-y","volume":"27","author":"F Gao","year":"2021","unstructured":"Gao F, Jia X, Zhao Z, Chen CC, Xu F, Geng Z, Song X (2021) Bibliometric analysis on tendency and topics of artificial intelligence over last decade. Microsyst Technol 27:1545\u20131557","journal-title":"Microsyst Technol"},{"issue":"2","key":"7021_CR23","doi-asserted-by":"publisher","first-page":"1699","DOI":"10.1007\/s10462-022-10206-4","volume":"56","author":"IM De la Vega Hern\u00e1ndez","year":"2023","unstructured":"De la Vega Hern\u00e1ndez IM, Urdaneta AS, Carayannis E (2023) Global bibliometric mapping of the frontier of knowledge in the field of artificial intelligence for the period 1990\u20132019. Artif Intell Rev 56(2):1699\u20131729","journal-title":"Artif Intell Rev"},{"issue":"3","key":"7021_CR24","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1007\/s12564-020-09640-2","volume":"21","author":"P Song","year":"2020","unstructured":"Song P, Wang X (2020) A bibliometric analysis of worldwide educational artificial intelligence research development in recent twenty years. Asia Pac Educ Rev 21(3):473\u2013486","journal-title":"Asia Pac Educ Rev"},{"issue":"6","key":"7021_CR25","doi-asserted-by":"publisher","first-page":"3695","DOI":"10.1007\/s11192-022-04406-6","volume":"127","author":"VZ Pessin","year":"2022","unstructured":"Pessin VZ, Yamane LH, Siman RR (2022) Smart bibliometrics: an integrated method of science mapping and bibliometric analysis. Scientometrics 127(6):3695\u20133718","journal-title":"Scientometrics"},{"key":"7021_CR26","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1016\/j.jbusres.2021.04.070","volume":"133","author":"N Donthu","year":"2021","unstructured":"Donthu N, Kumar S, Mukherjee D, Pandey N, Lim WM (2021) How to conduct a bibliometric analysis: an overview and guidelines. J Bus Res 133:285\u2013296","journal-title":"J Bus Res"},{"issue":"2","key":"7021_CR27","doi-asserted-by":"publisher","first-page":"120","DOI":"10.22456\/2175-2745.140214","volume":"31","author":"NLB Souza","year":"2024","unstructured":"Souza NLB, Lima DA (2024) Systematic literature review on the application of controllers based on cellular automata in robotic tasks. Rev Inform Te\u00f3r Apl 31(2):120\u2013137","journal-title":"Rev Inform Te\u00f3r Apl"},{"issue":"2","key":"7021_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3485275","volume":"31","author":"C Watson","year":"2022","unstructured":"Watson C, Cooper N, Palacio DN, Moran K, Poshyvanyk D (2022) A systematic literature review on the use of deep learning in software engineering research. ACM Trans Softw Eng Methodol (TOSEM) 31(2):1\u201358","journal-title":"ACM Trans Softw Eng Methodol (TOSEM)"},{"issue":"7","key":"7021_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1108\/INTR-08-2021-0600","volume":"32","author":"S Laato","year":"2022","unstructured":"Laato S, Tiainen M, Najmul Islam AKM, M\u00e4ntym\u00e4ki M (2022) How to explain AI systems to end users: a systematic literature review and research agenda. Internet Res 32(7):1\u201331","journal-title":"Internet Res"},{"issue":"1","key":"7021_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.giq.2022.101774","volume":"40","author":"R Madan","year":"2023","unstructured":"Madan R, Ashok M (2023) AI adoption and diffusion in public administration: a systematic literature review and future research agenda. Gov Inf Q 40(1):101774","journal-title":"Gov Inf Q"},{"key":"7021_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10660-020-09410-7","volume":"22","author":"X Ding","year":"2022","unstructured":"Ding X, Yang Z (2022) Knowledge mapping of platform research: a visual analysis using VOSviewer and CiteSpace. Electron Commer Res 22:1\u201323","journal-title":"Electron Commer Res"},{"key":"7021_CR32","doi-asserted-by":"publisher","first-page":"5113","DOI":"10.1007\/s11192-021-03948-5","volume":"126","author":"VK Singh","year":"2021","unstructured":"Singh VK, Singh P, Karmakar M, Leta J, Mayr P (2021) The journal coverage of web of science, scopus and dimensions: a comparative analysis. Scientometrics 126:5113\u20135142","journal-title":"Scientometrics"},{"key":"7021_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115728","volume":"186","author":"M Su","year":"2021","unstructured":"Su M, Peng H, Li S (2021) A visualized bibliometric analysis of mapping research trends of machine learning in engineering (MLE). Expert Syst Appl 186:115728","journal-title":"Expert Syst Appl"},{"issue":"4","key":"7021_CR34","volume":"2","author":"Y Xu","year":"2021","unstructured":"Xu Y, Liu X, Cao X, Huang C, Liu E, Qian S, Zhang J (2021) Artificial intelligence: a powerful paradigm for scientific research. Innovation 2(4):100179","journal-title":"Innovation"},{"key":"7021_CR35","unstructured":"McMahan B, Moore E, Ramage D, Hampson S, y Arcas BA (2017) Communication-efficient learning of deep networks from decentralized data. In: Artificial intelligence and statistics. PMLR, pp 1273\u20131282"},{"key":"7021_CR36","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/BF02478259","volume":"5","author":"WS McCulloch","year":"1943","unstructured":"McCulloch WS, Pitts W (1943) A logical calculus of the ideas immanent in nervous activity. Bull Math Biophys 5:115\u2013133","journal-title":"Bull Math Biophys"},{"issue":"1\u20132","key":"7021_CR37","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/0004-3702(78)90010-3","volume":"11","author":"BG Buchanan","year":"1978","unstructured":"Buchanan BG, Feigenbaum EA (1978) DENDRAL and Meta-DENDRAL: their applications dimension. Artif Intell 11(1\u20132):5\u201324","journal-title":"Artif Intell"},{"issue":"7623","key":"7021_CR38","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1038\/538020a","volume":"538","author":"D Castelvecchi","year":"2016","unstructured":"Castelvecchi D (2016) Can we open the black box of AI? Nat News 538(7623):20","journal-title":"Nat News"},{"issue":"7","key":"7021_CR39","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Osindero S, Teh YW (2006) A fast learning algorithm for deep belief nets. Neural Comput 18(7):1527\u20131554","journal-title":"Neural Comput"},{"issue":"7553","key":"7021_CR40","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436\u2013444","journal-title":"Nature"},{"key":"7021_CR41","doi-asserted-by":"crossref","unstructured":"Soni N, Sharma EK, Singh N, Kapoor A (2019) Impact of artificial intelligence on businesses: from research, innovation, market deployment to future shifts in business models. arXiv preprint arXiv:1905.02092","DOI":"10.1016\/j.procs.2020.03.272"},{"key":"7021_CR42","doi-asserted-by":"crossref","unstructured":"Xia B, Wang X, Yamasaki T, Aizawa K, Seshime H (2019) Deep neural network-based click-through rate prediction using multimodal features of online banners. In: 2019 IEEE 5th International Conference on Multimedia Big Data (BigMM). IEEE, pp 162\u2013170","DOI":"10.1109\/BigMM.2019.00-29"},{"key":"7021_CR43","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, and Polosukhin I (2017) Attention is all you need. In: Advances in Neural Information Processing Systems, vol 30"},{"key":"7021_CR44","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD, Dhariwal P, Amodei D (2020) Language models are few-shot learners. Adv Neural Inf Process Syst 33:1877\u20131901","journal-title":"Adv Neural Inf Process Syst"},{"issue":"4","key":"7021_CR45","first-page":"12","volume":"27","author":"J McCarthy","year":"2006","unstructured":"McCarthy J, Minsky ML, Rochester N, Shannon CE (2006) A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI Mag 27(4):12\u201312","journal-title":"AI Mag"},{"issue":"3","key":"7021_CR46","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TIT.1956.1056797","volume":"2","author":"H Simon","year":"1956","unstructured":"Simon H (1956) The logic theory machine\u2013a complex information processing system. IEEE Trans Inf Theory 2(3):61\u201379","journal-title":"IEEE Trans Inf Theory"},{"issue":"1","key":"7021_CR47","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1145\/365153.365168","volume":"9","author":"J Weizenbaum","year":"1966","unstructured":"Weizenbaum J (1966) ELIZA-a computer program for the study of natural language communication between man and machine. Commun ACM 9(1):36\u201345","journal-title":"Commun ACM"},{"key":"7021_CR48","unstructured":"Shortliffe EH, Buchanan BG (1990) A model of inexact reasoning in medicine. In: Readings in Uncertain Reasoning, pp 259\u2013275"},{"issue":"7587","key":"7021_CR49","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1038\/nature16961","volume":"529","author":"D Silver","year":"2016","unstructured":"Silver D, Huang A, Maddison CJ, Guez A, Sifre L, Van Den Driessche G, Hassabis D (2016) Mastering the game of go with deep neural networks and tree search. Nature 529(7587):484\u2013489","journal-title":"Nature"},{"issue":"9","key":"7021_CR50","doi-asserted-by":"publisher","first-page":"13954","DOI":"10.1109\/TITS.2021.3127217","volume":"23","author":"Z Tan","year":"2021","unstructured":"Tan Z, Dai N, Su Y, Zhang R, Li Y, Wu D, Li S (2021) Human-machine interaction in intelligent and connected vehicles: a review of status quo, issues, and opportunities. IEEE Trans Intell Transp Syst 23(9):13954\u201313975","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"8","key":"7021_CR51","first-page":"9","volume":"1","author":"A Radford","year":"2019","unstructured":"Radford A, Wu J, Child R, Luan D, Amodei D, Sutskever I (2019) Language models are unsupervised multitask learners. OpenAI Blog 1(8):9","journal-title":"OpenAI Blog"},{"issue":"6245","key":"7021_CR52","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1126\/science.aaa8403","volume":"349","author":"DC Parkes","year":"2015","unstructured":"Parkes DC, Wellman MP (2015) Economic reasoning and artificial intelligence. Science 349(6245):267\u2013272","journal-title":"Science"},{"issue":"1","key":"7021_CR53","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.aac.2022.10.001","volume":"2","author":"M Javaid","year":"2023","unstructured":"Javaid M, Haleem A, Khan IH, Suman R (2023) Understanding the potential applications of artificial intelligence in agriculture sector. Adv Agrochem 2(1):15\u201330","journal-title":"Adv Agrochem"},{"key":"7021_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12541-021-00600-3","volume":"23","author":"SW Kim","year":"2022","unstructured":"Kim SW, Kong JH, Lee SW, Lee S (2022) Recent advances of artificial intelligence in manufacturing industrial sectors: a review. Int J Precis Eng Manuf 23:1\u201319","journal-title":"Int J Precis Eng Manuf"},{"issue":"2","key":"7021_CR55","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1109\/TEM.2020.2989214","volume":"69","author":"C M\u00fchlroth","year":"2020","unstructured":"M\u00fchlroth C, Grottke M (2020) Artificial intelligence in innovation: how to spot emerging trends and technologies. IEEE Trans Eng Manag 69(2):493\u2013510","journal-title":"IEEE Trans Eng Manag"},{"key":"7021_CR56","volume":"38","author":"R Desislavov","year":"2023","unstructured":"Desislavov R, Mart\u00ednez-Plumed F, Hern\u00e1ndez-Orallo J (2023) Trends in AI inference energy consumption: beyond the performance-vs-parameter laws of deep learning. Sustain Comput Inform Syst 38:100857","journal-title":"Sustain Comput Inform Syst"},{"key":"7021_CR57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11356-024-32404-z","volume":"31","author":"AK Wani","year":"2024","unstructured":"Wani AK, Rahayu F, Ben Amor I, Quadir M, Murianingrum M, Parnidi P, Latifah E (2024) Environmental resilience through artificial intelligence: innovations in monitoring and management. Environ Sci Pollut Res 31:1\u201317","journal-title":"Environ Sci Pollut Res"},{"issue":"3","key":"7021_CR58","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s42979-021-00557-0","volume":"2","author":"IH Sarker","year":"2021","unstructured":"Sarker IH, Furhad MH, Nowrozy R (2021) Ai-driven cybersecurity: an overview, security intelligence modeling and research directions. SN Comput Sci 2(3):173","journal-title":"SN Comput Sci"},{"key":"7021_CR59","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s43681-020-00002-7","volume":"1","author":"J Borenstein","year":"2021","unstructured":"Borenstein J, Howard A (2021) Emerging challenges in AI and the need for AI ethics education. AI Ethics 1:61\u201365","journal-title":"AI Ethics"},{"issue":"1","key":"7021_CR60","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1038\/s41591-021-01614-0","volume":"28","author":"P Rajpurkar","year":"2022","unstructured":"Rajpurkar P, Chen E, Banerjee O, Topol EJ (2022) AI in health and medicine. Nat Med 28(1):31\u201338","journal-title":"Nat Med"},{"issue":"6","key":"7021_CR61","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3457607","volume":"54","author":"N Mehrabi","year":"2021","unstructured":"Mehrabi N, Morstatter F, Saxena N, Lerman K, Galstyan A (2021) A survey on bias and fairness in machine learning. ACM Comput Surv (CSUR) 54(6):1\u201335","journal-title":"ACM Comput Surv (CSUR)"},{"key":"7021_CR62","doi-asserted-by":"publisher","DOI":"10.1016\/j.bios.2020.112412","volume":"165","author":"X Jin","year":"2020","unstructured":"Jin X, Liu C, Xu T, Su L, Zhang X (2020) Artificial intelligence biosensors: challenges and prospects. Biosens Bioelectron 165:112412","journal-title":"Biosens Bioelectron"},{"issue":"8","key":"7021_CR63","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1038\/s42256-022-00516-1","volume":"4","author":"W Liang","year":"2022","unstructured":"Liang W, Tadesse GA, Ho D, Fei-Fei L, Zaharia M, Zhang C, Zou J (2022) Advances, challenges and opportunities in creating data for trustworthy AI. Nat Mach Intell 4(8):669\u2013677","journal-title":"Nat Mach Intell"},{"issue":"1","key":"7021_CR64","first-page":"214","volume":"614","author":"A Jo","year":"2023","unstructured":"Jo A (2023) The promise and peril of generative AI. Nature 614(1):214\u2013216","journal-title":"Nature"},{"key":"7021_CR65","doi-asserted-by":"crossref","unstructured":"Xu F, Uszkoreit H, Du Y, Fan W, Zhao D, Zhu J (2019) Explainable AI: a brief survey on history, research areas, approaches and challenges. In: Natural Language Processing and Chinese Computing: 8th CCF International Conference, NLPCC 2019, Dunhuang, China, October 9\u201314, 2019, Proceedings, Part II 8. Springer, pp 563\u2013574","DOI":"10.1007\/978-3-030-32236-6_51"},{"issue":"1","key":"7021_CR66","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1162\/qss_a_00019","volume":"1","author":"J Baas","year":"2020","unstructured":"Baas J, Schotten M, Plume A, C\u00f4t\u00e9 G, Karimi R (2020) Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quant Sci Stud 1(1):377\u2013386","journal-title":"Quant Sci Stud"},{"issue":"4","key":"7021_CR67","doi-asserted-by":"publisher","DOI":"10.1016\/j.ibusrev.2020.101709","volume":"29","author":"S Srivastava","year":"2020","unstructured":"Srivastava S, Singh S, Dhir S (2020) Culture and International business research: a review and research agenda. Int Bus Rev 29(4):101709","journal-title":"Int Bus Rev"},{"issue":"1","key":"7021_CR68","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1007\/s11192-020-03690-4","volume":"126","author":"A Mart\u00edn-Mart\u00edn","year":"2021","unstructured":"Mart\u00edn-Mart\u00edn A, Thelwall M, Orduna-Malea E, Delgado L\u00f3pez-C\u00f3zar E (2021) Google scholar, microsoft academic, scopus, dimensions, web of science, and OpenCitations\u2019 COCI: a multidisciplinary comparison of coverage via citations. Scientometrics 126(1):871\u2013906","journal-title":"Scientometrics"},{"issue":"1","key":"7021_CR69","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3390\/publications9010012","volume":"9","author":"R Pranckut\u0117","year":"2021","unstructured":"Pranckut\u0117 R (2021) Web of science (WoS) and scopus: the titans of bibliographic information in today\u2019s academic world. Publications 9(1):12","journal-title":"Publications"},{"issue":"2","key":"7021_CR70","first-page":"107","volume":"11","author":"R Verma","year":"2022","unstructured":"Verma R, Sharma S (2022) Scopus: a comprehensive literature review. Int J Prof Dev 11(2):107\u2013110","journal-title":"Int J Prof Dev"},{"issue":"1","key":"7021_CR71","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1162\/qss_a_00112","volume":"2","author":"M Visser","year":"2021","unstructured":"Visser M, Van Eck NJ, Waltman L (2021) Large-scale comparison of bibliographic data sources: scopus, web of science, dimensions, crossref, and microsoft academic. Quant Sci Stud 2(1):20\u201341","journal-title":"Quant Sci Stud"},{"issue":"7","key":"7021_CR72","doi-asserted-by":"publisher","first-page":"3769","DOI":"10.1007\/s11192-024-05034-y","volume":"129","author":"JL Ortega","year":"2024","unstructured":"Ortega JL, Delgado-Quir\u00f3s L (2024) The indexation of retracted literature in seven principal scholarly databases: a coverage comparison of dimensions, OpenAlex, PubMed, Scilit, Scopus, The Lens and Web of Science. Scientometrics 129(7):3769\u20133785","journal-title":"Scientometrics"},{"issue":"4","key":"7021_CR73","doi-asserted-by":"publisher","first-page":"1069","DOI":"10.1108\/BIJ-01-2021-0009","volume":"29","author":"RN Chawla","year":"2022","unstructured":"Chawla RN, Goyal P (2022) Emerging trends in digital transformation: a bibliometric analysis. Benchmarking Int J 29(4):1069\u20131112","journal-title":"Benchmarking Int J"},{"issue":"1","key":"7021_CR74","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1007\/s11192-020-03734-9","volume":"126","author":"I Basson","year":"2021","unstructured":"Basson I, Blanckenberg JP, Prozesky H (2021) Do open access journal articles experience a citation advantage? Results and methodological reflections of an application of multiple measures to an analysis by WoS subject areas. Scientometrics 126(1):459\u2013484","journal-title":"Scientometrics"},{"issue":"8","key":"7021_CR75","doi-asserted-by":"publisher","first-page":"1798","DOI":"10.1109\/TPAMI.2013.50","volume":"35","author":"Y Bengio","year":"2013","unstructured":"Bengio Y, Courville A, Vincent P (2013) Representation learning: A review and new perspectives. IEEE Trans Pattern Anal Mach Intell 35(8):1798\u20131828","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"5","key":"7021_CR76","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1109\/TMI.2016.2528162","volume":"35","author":"HC Shin","year":"2016","unstructured":"Shin HC, Roth HR, Gao M, Lu L, Xu Z, Nogues I, Summers RM (2016) Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning. IEEE Trans Med Imaging 35(5):1285\u20131298","journal-title":"IEEE Trans Med Imaging"},{"issue":"10","key":"7021_CR77","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","volume":"28","author":"K Greff","year":"2016","unstructured":"Greff K, Srivastava RK, Koutn\u00edk J, Steunebrink BR, Schmidhuber J (2016) LSTM: a search space odyssey. IEEE Trans Neural Netw Learn Syst 28(10):2222\u20132232","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"1","key":"7021_CR78","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2012","unstructured":"Liu G, Lin Z, Yan S, Sun J, Yu Y, Ma Y (2012) Robust recovery of subspace structures by low-rank representation. IEEE Trans Pattern Anal Mach Intell 35(1):171\u2013184","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"7021_CR79","doi-asserted-by":"publisher","first-page":"2765","DOI":"10.1109\/TPAMI.2013.57","volume":"35","author":"E Elhamifar","year":"2013","unstructured":"Elhamifar E, Vidal R (2013) Sparse subspace clustering: algorithm, theory, and applications. IEEE Trans Pattern Anal Mach Intell 35(11):2765\u20132781","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"7021_CR80","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","volume":"187","author":"Y Guo","year":"2016","unstructured":"Guo Y, Liu Y, Oerlemans A, Lao S, Wu S, Lew MS (2016) Deep learning for visual understanding: a review. Neurocomputing 187:27\u201348","journal-title":"Neurocomputing"},{"key":"7021_CR81","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10462-012-9328-0","volume":"42","author":"D Karaboga","year":"2014","unstructured":"Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif Intell Rev 42:21\u201357","journal-title":"Artif Intell Rev"},{"issue":"1","key":"7021_CR82","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1109\/TPAMI.2012.39","volume":"35","author":"J Liu","year":"2012","unstructured":"Liu J, Musialski P, Wonka P, Ye J (2012) Tensor completion for estimating missing values in visual data. IEEE Trans Pattern Anal Mach Intell 35(1):208\u2013220","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"7021_CR83","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/JBHI.2016.2636665","volume":"21","author":"D Rav\u00ec","year":"2016","unstructured":"Rav\u00ec D, Wong C, Deligianni F, Berthelot M, Andreu-Perez J, Lo B, Yang GZ (2016) Deep learning for health informatics. IEEE J Biomed Health Inform 21(1):4\u201321","journal-title":"IEEE J Biomed Health Inform"},{"key":"7021_CR84","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.neucom.2017.11.077","volume":"300","author":"J Cai","year":"2018","unstructured":"Cai J, Luo J, Wang S, Yang S (2018) Feature selection in machine learning: a new perspective. Neurocomputing 300:70\u201379","journal-title":"Neurocomputing"},{"key":"7021_CR85","doi-asserted-by":"crossref","unstructured":"Chen T, Guestrin C (2016) Xgboost: a scalable tree boosting system. In: Proceedings of the 22nd ACM Sigkdd International Conference on Knowledge Discovery and Data Mining, pp 785\u2013794","DOI":"10.1145\/2939672.2939785"},{"key":"7021_CR86","unstructured":"Ioffe S (2015) Batch normalization: accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167"},{"key":"7021_CR87","doi-asserted-by":"crossref","unstructured":"Ribeiro MT, Singh S, Guestrin C (2016) Why should i trust you? Explaining the predictions of any classifier. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp 1135\u20131144","DOI":"10.1145\/2939672.2939778"},{"key":"7021_CR88","doi-asserted-by":"crossref","unstructured":"Szegedy C, Ioffe S, Vanhoucke V, Alemi A (2017) Inception-v4, inception-resnet and the impact of residual connections on learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol 31, no 1","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"7021_CR89","unstructured":"Arjovsky M, Chintala S, Bottou L (2017) Wasserstein generative adversarial networks. In: International Conference on Machine Learning. PMLR, pp 214\u2013223"},{"key":"7021_CR90","unstructured":"Schulman J (2015) Trust region policy optimization. arXiv preprint arXiv:1502.05477"},{"key":"7021_CR91","unstructured":"Xu K (2015) Show, attend and tell: neural image caption generation with visual attention. arXiv preprint arXiv:1502.03044"},{"key":"7021_CR92","unstructured":"Shi X, Chen Z, Wang H, Yeung DY, Wong WK, Woo WC (2015) Convolutional LSTM network: a machine learning approach for precipitation nowcasting. In: Advances in Neural Information Processing Systems, vol 28"},{"key":"7021_CR93","doi-asserted-by":"crossref","unstructured":"Van Hasselt H, Guez A, Silver D (2016) Deep reinforcement learning with double q-learning. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol 30, no 1","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"7021_CR94","doi-asserted-by":"crossref","unstructured":"Vinyals O, Toshev A, Bengio S, Erhan D (2015) Show and tell: a neural image caption generator. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 3156\u20133164","DOI":"10.1109\/CVPR.2015.7298935"},{"key":"7021_CR95","unstructured":"Ganin Y, Lempitsky V (2015) Unsupervised domain adaptation by backpropagation. In: International Conference on Machine Learning. PMLR, pp 1180\u20131189"},{"key":"7021_CR96","unstructured":"Finn C, Abbeel P, Levine S (2017) Model-agnostic meta-learning for fast adaptation of deep networks. In: International Conference on Machine Learning. PMLR, pp 1126\u20131135"},{"key":"7021_CR97","doi-asserted-by":"crossref","unstructured":"Zheng Z, Wang P, Liu W, Li J, Ye R, Ren D (2020) Distance-IoU loss: faster and better learning for bounding box regression. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol 34, no 07, pp 12993\u201313000","DOI":"10.1609\/aaai.v34i07.6999"},{"key":"7021_CR98","doi-asserted-by":"crossref","unstructured":"Papernot N, McDaniel P, Jha S, Fredrikson M, Celik ZB, Swami A (2016) The limitations of deep learning in adversarial settings. In: 2016 IEEE European Symposium on Security and Privacy (EuroS &P). IEEE, pp 372\u2013387","DOI":"10.1109\/EuroSP.2016.36"},{"key":"7021_CR99","doi-asserted-by":"crossref","unstructured":"Abadi M, Chu A, Goodfellow I, McMahan HB, Mironov I, Talwar K, Zhang L (2016) Deep learning with differential privacy. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp 308\u2013318","DOI":"10.1145\/2976749.2978318"},{"key":"7021_CR100","unstructured":"Touvron H, Cord M, Douze M, Massa F, Sablayrolles A, J\u00e9gou H (2021) Training data-efficient image transformers & distillation through attention. In: International Conference on Machine Learning. PMLR, pp 10347\u201310357"},{"key":"7021_CR101","unstructured":"Long M, Cao Y, Wang J, Jordan M (2015) Learning transferable features with deep adaptation networks. In: International Conference on Machine Learning. PMLR, pp 97\u2013105"},{"key":"7021_CR102","doi-asserted-by":"crossref","unstructured":"Hutto C, Gilbert E (2014) Vader: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the International AAAI Conference on Web and Social Media, vol 8, no 1, pp 216\u2013225","DOI":"10.1609\/icwsm.v8i1.14550"},{"key":"7021_CR103","doi-asserted-by":"crossref","unstructured":"Yan S, Xiong Y, Lin D (2018) Spatial temporal graph convolutional networks for skeleton-based action recognition. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol 32, no 1","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"7021_CR104","first-page":"1","volume":"36","author":"PK Pandey","year":"2022","unstructured":"Pandey PK, Bajpai N (2022) Mapping the research pattern of cause-related marketing: a bibliometric analysis of publications during 2000\u20132020. J Nonprofit Public Sect Mark 36:1\u201328","journal-title":"J Nonprofit Public Sect Mark"},{"issue":"14","key":"7021_CR105","doi-asserted-by":"publisher","first-page":"16301","DOI":"10.1109\/JSEN.2021.3076767","volume":"21","author":"R Kumar","year":"2021","unstructured":"Kumar R, Khan AA, Kumar J, Golilarz NA, Zhang S, Ting Y, Wang W (2021) Blockchain-federated-learning and deep learning models for COVID-19 detection using CT imaging. IEEE Sens J 21(14):16301\u201316314","journal-title":"IEEE Sens J"},{"issue":"1","key":"7021_CR106","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1007\/s44196-023-00233-6","volume":"16","author":"S Lu","year":"2023","unstructured":"Lu S, Ding Y, Liu M, Yin Z, Yin L, Zheng W (2023) Multiscale feature extraction and fusion of image and text in VQA. Int J Comput Intell Syst 16(1):54","journal-title":"Int J Comput Intell Syst"},{"issue":"3","key":"7021_CR107","doi-asserted-by":"publisher","first-page":"1069","DOI":"10.1007\/s11831-020-09413-5","volume":"28","author":"G Kumar","year":"2021","unstructured":"Kumar G, Jain S, Singh UP (2021) Stock market forecasting using computational intelligence: a survey. Arch Comput Methods Eng 28(3):1069\u20131101","journal-title":"Arch Comput Methods Eng"},{"issue":"7","key":"7021_CR108","doi-asserted-by":"publisher","first-page":"914","DOI":"10.1631\/FITEE.1700822","volume":"20","author":"XL Zheng","year":"2019","unstructured":"Zheng XL, Zhu MY, Li QB, Chen CC, Tan YC (2019) FinBrain: when finance meets AI 2.0. Front Inf Technol Electron Eng 20(7):914\u2013924","journal-title":"Front Inf Technol Electron Eng"},{"issue":"7945","key":"7021_CR109","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1038\/s41586-022-05639-4","volume":"613","author":"J Bur\u00e9s","year":"2023","unstructured":"Bur\u00e9s J, Larrosa I (2023) Organic reaction mechanism classification using machine learning. Nature 613(7945):689\u2013695","journal-title":"Nature"},{"issue":"1","key":"7021_CR110","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1109\/JAS.2023.123741","volume":"11","author":"C Liu","year":"2024","unstructured":"Liu C, Wang Y, Yang C, Gui W (2024) Multimodal data-driven reinforcement learning for operational decision-making in industrial processes. IEEE\/CAA J Autom Sin 11(1):252\u2013254","journal-title":"IEEE\/CAA J Autom Sin"},{"issue":"5","key":"7021_CR111","doi-asserted-by":"publisher","first-page":"4067","DOI":"10.1109\/TPWRS.2022.3142969","volume":"37","author":"L Yang","year":"2022","unstructured":"Yang L, Sun Q, Zhang N, Li Y (2022) Indirect multi-energy transactions of energy internet with deep reinforcement learning approach. IEEE Trans Power Syst 37(5):4067\u20134077","journal-title":"IEEE Trans Power Syst"},{"key":"7021_CR112","doi-asserted-by":"crossref","unstructured":"Alrahis L, Knechtel J, Sinanoglu O (2023) Graph neural networks: a powerful and versatile tool for advancing design, reliability, and security of ICs. In: Proceedings of the 28th Asia and South Pacific Design Automation Conference, pp 83\u201390","DOI":"10.1145\/3566097.3568345"},{"issue":"8","key":"7021_CR113","doi-asserted-by":"publisher","first-page":"3800","DOI":"10.1109\/TKDE.2020.3025588","volume":"34","author":"D Cheng","year":"2020","unstructured":"Cheng D, Wang X, Zhang Y, Zhang L (2020) Graph neural network for fraud detection via spatial-temporal attention. IEEE Trans Knowl Data Eng 34(8):3800\u20133813","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"2","key":"7021_CR114","doi-asserted-by":"publisher","first-page":"35","DOI":"10.3390\/ijgi12020035","volume":"12","author":"M Andronie","year":"2023","unstructured":"Andronie M, L\u0103z\u0103roiu G, Iatagan M, Hurloiu I, \u0218tef\u0103nescu R, Dijm\u0103rescu A, Dijm\u0103rescu I (2023) Big data management algorithms, deep learning-based object detection technologies, and geospatial simulation and sensor fusion tools in the internet of robotic things. ISPRS Int J Geo Inf 12(2):35","journal-title":"ISPRS Int J Geo Inf"},{"issue":"3","key":"7021_CR115","doi-asserted-by":"publisher","first-page":"1563","DOI":"10.1007\/s11192-020-03371-2","volume":"122","author":"DR Raban","year":"2020","unstructured":"Raban DR, Gordon A (2020) The evolution of data science and big data research: a bibliometric analysis. Scientometrics 122(3):1563\u20131581","journal-title":"Scientometrics"},{"key":"7021_CR116","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1016\/j.inffus.2022.09.025","volume":"91","author":"A Gandhi","year":"2023","unstructured":"Gandhi A, Adhvaryu K, Poria S, Cambria E, Hussain A (2023) Multimodal sentiment analysis: a systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions. Inf Fusion 91:424\u2013444","journal-title":"Inf Fusion"},{"key":"7021_CR117","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2020.103625","volume":"92","author":"AK Shukla","year":"2020","unstructured":"Shukla AK, Muhuri PK, Abraham A (2020) A bibliometric analysis and cutting-edge overview on fuzzy techniques in big data. Eng Appl Artif Intell 92:103625","journal-title":"Eng Appl Artif Intell"},{"key":"7021_CR118","doi-asserted-by":"publisher","first-page":"21502","DOI":"10.1109\/JIOT.2023.3296469","volume":"10","author":"J Cai","year":"2023","unstructured":"Cai J, Liang W, Li X, Li K, Gui Z, Khan MK (2023) GTxChain: a secure IoT smart blockchain architecture based on graph neural network. IEEE Internet Things J 10:21502","journal-title":"IEEE Internet Things J"},{"key":"7021_CR119","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.ins.2022.11.139","volume":"622","author":"AM Ikotun","year":"2023","unstructured":"Ikotun AM, Ezugwu AE, Abualigah L, Abuhaija B, Heming J (2023) K-means clustering algorithms: a comprehensive review, variants analysis, and advances in the era of big data. Inf Sci 622:178\u2013210","journal-title":"Inf Sci"},{"key":"7021_CR120","doi-asserted-by":"publisher","first-page":"8681","DOI":"10.1109\/TWC.2023.3264752","volume":"22","author":"M Ouyang","year":"2023","unstructured":"Ouyang M, Gao F, Wang Y, Zhang S, Li P, Ren J (2023) Computer vision-aided reconfigurable intelligent surface-based beam tracking: prototyping and experimental results. IEEE Trans Wirel Commun 22:8681","journal-title":"IEEE Trans Wirel Commun"},{"key":"7021_CR121","doi-asserted-by":"publisher","first-page":"2807","DOI":"10.1007\/s13042-020-01152-0","volume":"11","author":"Y Li","year":"2020","unstructured":"Li Y, Xu Z, Wang X, Wang X (2020) A bibliometric analysis on deep learning during 2007\u20132019. Int J Mach Learn Cybern 11:2807\u20132826","journal-title":"Int J Mach Learn Cybern"},{"issue":"9","key":"7021_CR122","doi-asserted-by":"publisher","first-page":"10345","DOI":"10.1007\/s10462-023-10419-1","volume":"56","author":"DS Asudani","year":"2023","unstructured":"Asudani DS, Nagwani NK, Singh P (2023) Impact of word embedding models on text analytics in deep learning environment: a review. Artif Intell Rev 56(9):10345\u201310425","journal-title":"Artif Intell Rev"},{"key":"7021_CR123","doi-asserted-by":"publisher","first-page":"3663","DOI":"10.1016\/j.matpr.2021.07.357","volume":"80","author":"AH Shamman","year":"2023","unstructured":"Shamman AH, Hadi AA, Ramul AR, Zahra MMA, Gheni HM (2023) The artificial intelligence (AI) role for tackling against COVID-19 pandemic. Mater Today Proc 80:3663\u20133667","journal-title":"Mater Today Proc"},{"issue":"1","key":"7021_CR124","doi-asserted-by":"publisher","first-page":"15836","DOI":"10.1038\/s41598-022-20168-w","volume":"12","author":"M Xia","year":"2022","unstructured":"Xia M, Kheterpal MK, Wong SC, Park C, Ratliff W, Carin L, Henao R (2022) Lesion identification and malignancy prediction from clinical dermatological images. Sci Rep 12(1):15836","journal-title":"Sci Rep"},{"key":"7021_CR125","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2019.102526","volume":"153","author":"D Gibert","year":"2020","unstructured":"Gibert D, Mateu C, Planes J (2020) The rise of machine learning for detection and classification of malware: research developments, trends and challenges. J Netw Comput Appl 153:102526","journal-title":"J Netw Comput Appl"},{"key":"7021_CR126","doi-asserted-by":"publisher","first-page":"2947","DOI":"10.1109\/TASLP.2023.3293046","volume":"31","author":"H Liu","year":"2023","unstructured":"Liu H, Liu J, Cui L, Teng Z, Duan N, Zhou M, Zhang Y (2023) Logiqa 2.0-an improved dataset for logical reasoning in natural language understanding. IEEE\/ACM Trans Audio Speech Lang Process 31:2947","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"issue":"9","key":"7021_CR127","doi-asserted-by":"publisher","first-page":"6092","DOI":"10.1109\/TII.2020.2974555","volume":"16","author":"PCM Arachchige","year":"2020","unstructured":"Arachchige PCM, Bertok P, Khalil I, Liu D, Camtepe S, Atiquzzaman M (2020) A trustworthy privacy preserving framework for machine learning in industrial IoT systems. IEEE Trans Ind Inf 16(9):6092\u20136102","journal-title":"IEEE Trans Ind Inf"},{"issue":"1","key":"7021_CR128","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1002\/cjoc.202100456","volume":"40","author":"YP Huang","year":"2022","unstructured":"Huang YP, Xia Y, Yang L, Wei J, Yang YI, Gao YQ (2022) SPONGE: a GPU-accelerated molecular dynamics package with enhanced sampling and AI-driven algorithms. Chin J Chem 40(1):160\u2013168","journal-title":"Chin J Chem"},{"issue":"1","key":"7021_CR129","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","volume":"25","author":"EJ Topol","year":"2019","unstructured":"Topol EJ (2019) High-performance medicine: the convergence of human and artificial intelligence. Nat Med 25(1):44\u201356","journal-title":"Nat Med"},{"issue":"3","key":"7021_CR130","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1016\/j.eng.2019.12.015","volume":"6","author":"W Wu","year":"2020","unstructured":"Wu W, Huang T, Gong K (2020) Ethical principles and governance technology development of AI in China. Engineering 6(3):302\u2013309","journal-title":"Engineering"},{"key":"7021_CR131","doi-asserted-by":"publisher","DOI":"10.1016\/j.caeai.2022.100068","volume":"3","author":"A Bhutoria","year":"2022","unstructured":"Bhutoria A (2022) Personalized education and artificial intelligence in the United States, China, and India: a systematic review using a human-in-the-loop model. Comput Educ Artif Intell 3:100068","journal-title":"Comput Educ Artif Intell"},{"issue":"1","key":"7021_CR132","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3390\/joitmc7010071","volume":"7","author":"T Yigitcanlar","year":"2021","unstructured":"Yigitcanlar T, Corchado JM, Mehmood R, Li RYM, Mossberger K, Desouza K (2021) Responsible urban innovation with local government artificial intelligence (AI): a conceptual framework and research agenda. J Open Innov Technol Mark Complex 7(1):71","journal-title":"J Open Innov Technol Mark Complex"},{"issue":"1","key":"7021_CR133","first-page":"17","volume":"24","author":"Y Chawla","year":"2022","unstructured":"Chawla Y, Shimpo F, Soko\u0142owski MM (2022) Artificial intelligence and information management in the energy transition of India: lessons from the global IT heart. Digit Policy Regul Gov 24(1):17\u201329","journal-title":"Digit Policy Regul Gov"},{"key":"7021_CR134","first-page":"524","volume-title":"Advances in data science and artificial intelligence: ICDSAI 2022, IIT Patna, India, April 23\u201324","year":"2023","unstructured":"Misra R, Kesswani N, Rajarajan M, Veeravalli B, Brigui I, Patel A, Singh TN (eds) (2023) Advances in data science and artificial intelligence: ICDSAI 2022, IIT Patna, India, April 23\u201324. Springer, Cham, p 524"},{"issue":"7","key":"7021_CR135","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1038\/s41928-020-0435-7","volume":"3","author":"W Zhang","year":"2020","unstructured":"Zhang W, Gao B, Tang J, Yao P, Yu S, Chang MF, Wu H (2020) Neuro-inspired computing chips. Nat Electron 3(7):371\u2013382","journal-title":"Nat Electron"},{"key":"7021_CR136","doi-asserted-by":"publisher","DOI":"10.1016\/j.jrt.2020.100006","volume":"4","author":"K Wakunuma","year":"2020","unstructured":"Wakunuma K, Jiya T, Aliyu S (2020) Socio-ethical implications of using AI in accelerating SDG3 in least developed countries. J Responsib Technol 4:100006","journal-title":"J Responsib Technol"},{"issue":"3","key":"7021_CR137","first-page":"211","volume":"2","author":"N Mungoli","year":"2023","unstructured":"Mungoli N (2023) Leveraging AI and technology to address the challenges of underdeveloped countries. J Electr Electron Eng 2(3):211\u2013216","journal-title":"J Electr Electron Eng"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07021-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07021-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07021-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T16:49:49Z","timestamp":1740415789000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07021-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,24]]},"references-count":137,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["7021"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07021-3","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,24]]},"assertion":[{"value":"31 January 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"540"}}