{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:05:50Z","timestamp":1750309550388,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":24,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T00:00:00Z","timestamp":1723507200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"The CAMS Innovation Fund for Medical Sciences (CIFMS)","award":["2021-I2M-1-056"],"award-info":[{"award-number":["2021-I2M-1-056"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,13]]},"DOI":"10.1145\/3706890.3706910","type":"proceedings-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T13:37:20Z","timestamp":1736775440000},"page":"120-127","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Identification of Globally Leading Researchers in the Field of AI Medical Devices"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7595-4771","authenticated-orcid":false,"given":"Juan","family":"Chen","sequence":"first","affiliation":[{"name":"Institute of Medical Information & Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4753-8571","authenticated-orcid":false,"given":"Junyu","family":"Long","sequence":"additional","affiliation":[{"name":"School of Medical Humanity, Peking University Health Science Center, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9672-8310","authenticated-orcid":false,"given":"Lizi","family":"Pan","sequence":"additional","affiliation":[{"name":"Institute of Medical Information & Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8698-0485","authenticated-orcid":false,"given":"Zhuoting","family":"Li","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2220-3007","authenticated-orcid":false,"given":"Zhaolian","family":"Ouyang","sequence":"additional","affiliation":[{"name":"Institute of Medical Information & Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,1,13]]},"reference":[{"key":"e_1_3_3_1_1_2","doi-asserted-by":"crossref","unstructured":"Spyros Makridakis. 2017. The forthcoming Artificial Intelligence ( AI ) revolution : Its impact on society and firms. 46-60. 10.1016\/j.futures.2017.03.006.","DOI":"10.1016\/j.futures.2017.03.006"},{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Fei Wu Cewu Lu and Mingjie Zhu. 2020. Towards a new generation of artificial intelligence in China. 312-316. 10.1038\/s42256-020-0183-4.","DOI":"10.1038\/s42256-020-0183-4"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"crossref","unstructured":"Sara Migliorini. 2024. China's ' s Interim Measures on generative AI : Origin content and significance. 10.1016\/j.clsr.2024.105985.","DOI":"10.1016\/j.clsr.2024.105985"},{"key":"e_1_3_3_1_4_2","volume-title":"Artificial Intelligence and Japan's Fifth Generation : The Information Society, Neoliberalism, and Alternative Modernities (vol 88, pg 631","author":"Garvey Colin","year":"2019","unstructured":"Colin Garvey. 2020. Artificial Intelligence and Japan's Fifth Generation : The Information Society, Neoliberalism, and Alternative Modernities (vol 88, pg 631, 2019). 164. 10.1525\/phr.2020.89.1.164."},{"key":"e_1_3_3_1_5_2","volume-title":"Kakadiaris","author":"Gursoy Furkan","year":"2023","unstructured":"Furkan Gursoy, and Ioannis A. Kakadiaris. 2023. Artificial intelligence research strategy of the United States : critical assessment and policy recommendations. 10.3389\/fdata.2023.1206139."},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"crossref","unstructured":"Oskar J. Gstrein Noman Haleem and Andrej Zwitter. 2024. General-purpose AI regulation and the European Union AI Act. 10.14763\/2024.3.1790.","DOI":"10.14763\/2024.3.1790"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"Pranav Rajpurkar Emma Chen and Oishi Banerjee. 2022. AI in health and medicine. 31-38. 10.1038\/s41591-021-01614-0.","DOI":"10.1038\/s41591-021-01614-0"},{"key":"e_1_3_3_1_8_2","first-page":"1837","article-title":"AI in Medical Imaging Informatics","author":"Panayides A. S.","year":"2020","unstructured":"A. S. Panayides, A. Amini, and N. Filipovic. 2020. AI in Medical Imaging Informatics: Current Challenges and Future Directions. 1837-1857. 10.1109\/JBHI.2020.2991043.","journal-title":"Current Challenges and Future Directions."},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"crossref","unstructured":"Andrea Moglia Konstantinos Georgiou and Evangelos Georgiou. 2021. A systematic review on artificial intelligence in robot-assisted surgery. 10.1016\/j.ijsu.2021.106151.","DOI":"10.1016\/j.ijsu.2021.106151"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Xiayin Zhang Ziyue Ma and Huaijin Zheng. 2020. The combination of brain-computer interfaces and artificial intelligence: applications and challenges. 10.21037\/atm.2019.11.109.","DOI":"10.21037\/atm.2019.11.109"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"crossref","unstructured":"Chunhao Wang Chenyang Liu and Yushi Chang. 2020. Dose-Distribution-Driven PET Image-Based Outcome Prediction (DDD-PIOP): A Deep Learning Study for Oropharyngeal Cancer IMRT Application. 10.3389\/fonc.2020.01592.","DOI":"10.3389\/fonc.2020.01592"},{"key":"e_1_3_3_1_12_2","first-page":"12073223","article-title":"Recent Applications of Artificial Intelligence in Radiotherapy","volume":"10","author":"Santoro Miriam","year":"2022","unstructured":"Miriam Santoro, Silvia Strolin, and Giulia Paolani. 2022. Recent Applications of Artificial Intelligence in Radiotherapy: Where We Are and Beyond. 10.3390\/app12073223.","journal-title":"Where We Are and Beyond."},{"key":"e_1_3_3_1_13_2","unstructured":"Zhaomin Yao Hongyu Wang and Wencheng Yan. 2023. Artificial intelligence-based diagnosis of Alzheimer's disease with brain MRI images. 10.1016\/j.ejrad.2023.110934."},{"key":"e_1_3_3_1_14_2","volume-title":"BDHT: Generative AI Enables Causality Analysis for Mild Cognitive Impairment. 10.1109\/TASE.2024.3425949.","author":"Zuo Qiankun","year":"2024","unstructured":"Qiankun Zuo, Ling Chen, and Yanyan Shen. 2024. BDHT: Generative AI Enables Causality Analysis for Mild Cognitive Impairment. 10.1109\/TASE.2024.3425949."},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Manju Lata Joshi and Nehal Kanoongo. 2022. Depression detection using emotional artificial intelligence and machine learning: A closer review. 217-226. 10.1016\/j.matpr.2022.01.467.","DOI":"10.1016\/j.matpr.2022.01.467"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"crossref","unstructured":"Daniele Giansanti. 2023. An Umbrella Review of the Fusion of fMRI and AI in Autism. 10.3390\/diagnostics13233552.","DOI":"10.3390\/diagnostics13233552"},{"key":"e_1_3_3_1_17_2","first-page":"99","article-title":"Artificial Intelligence Applications in Pediatric Brain Tumor Imaging","author":"Huang Jonathan","year":"2022","unstructured":"Jonathan Huang, Nathan A. Shlobin, and Sandi K. Lam. 2022. Artificial Intelligence Applications in Pediatric Brain Tumor Imaging: A Systematic Review. 99-105. 10.1016\/j.wneu.2021.10.068.","journal-title":"A Systematic Review."},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"crossref","unstructured":"Xiujun Yang Aojie Li and Lihong Li. 2021. Multimodal Image Analysis of Sexual Dimorphism in Developing Childhood Brain. 257-268. 10.1007\/s10548-021-00823-7.","DOI":"10.1007\/s10548-021-00823-7"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"crossref","unstructured":"Andrew Lin Marton Kolossvary and Ivana Isgum. 2020. Artificial intelligence: improving the efficiency of cardiovascular imaging. 565-577. 10.1080\/17434440.2020.1777855.","DOI":"10.1080\/17434440.2020.1777855"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"Haidee Chen David Ouyang and Tina Baykaner. 2022. Artificial intelligence applications in cardio-oncology: Leveraging high dimensional cardiovascular data. 10.3389\/fcvm.2022.941148.","DOI":"10.3389\/fcvm.2022.941148"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"crossref","unstructured":"D. Merlin Praveena D. Angelin Sarah and S. Thomas George. 2022. Deep Learning Techniques for EEG Signal Applications - a Review. 3030-3037. 10.1080\/03772063.2020.1749143.","DOI":"10.1080\/03772063.2020.1749143"},{"key":"e_1_3_3_1_22_2","unstructured":"Mohammad Mahbubur Rahman Khan Mamun and Tarek Elfouly. 2023. AI-Enabled Electrocardiogram Analysis for Disease Diagnosis. 10.3390\/asi6050095."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"crossref","unstructured":"Ankit Vijayvargiya Puneet Singh and Rajesh Kumar. 2022. Hardware Implementation for Lower Limb Surface EMG Measurement and Analysis Using Explainable AI for Activity Recognition. 10.1109\/TIM.2022.3198443.","DOI":"10.1109\/TIM.2022.3198443"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"crossref","unstructured":"Dimitrios Kolosov Vasilios Kelefouras and Pandelis Kourtessis. 2023. Contactless Camera-Based Heart Rate and Respiratory Rate Monitoring Using AI on Hardware. 10.3390\/s23094550.","DOI":"10.3390\/s23094550"}],"event":{"name":"ISAIMS 2024: 2024 5th International Symposium on Artificial Intelligence for Medicine Science","acronym":"ISAIMS 2024","location":"Amsterdam Netherlands"},"container-title":["Proceedings of the 2024 5th International Symposium on Artificial Intelligence for Medicine Science"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706890.3706910","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3706890.3706910","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:46Z","timestamp":1750295926000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706890.3706910"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,13]]},"references-count":24,"alternative-id":["10.1145\/3706890.3706910","10.1145\/3706890"],"URL":"https:\/\/doi.org\/10.1145\/3706890.3706910","relation":{},"subject":[],"published":{"date-parts":[[2024,8,13]]},"assertion":[{"value":"2025-01-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}