{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T18:58:39Z","timestamp":1782327519144,"version":"3.54.5"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,5,30]],"date-time":"2020-05-30T00:00:00Z","timestamp":1590796800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,5,30]],"date-time":"2020-05-30T00:00:00Z","timestamp":1590796800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s11227-020-03347-2","type":"journal-article","created":{"date-parts":[[2020,5,30]],"date-time":"2020-05-30T07:02:36Z","timestamp":1590822156000},"page":"1998-2017","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":115,"title":["An AI-based intelligent system for healthcare analysis using Ridge-Adaline Stochastic Gradient Descent Classifier"],"prefix":"10.1007","volume":"77","author":[{"given":"N.","family":"Deepa","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B.","family":"Prabadevi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Praveen Kumar","family":"Maddikunta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0097-801X","authenticated-orcid":false,"given":"Thippa Reddy","family":"Gadekallu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thar","family":"Baker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. Ajmal","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Usman","family":"Tariq","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,5,30]]},"reference":[{"key":"3347_CR1","doi-asserted-by":"publisher","first-page":"106917","DOI":"10.1016\/j.csda.2020.106917","volume":"145","author":"A Bedoui","year":"2020","unstructured":"Bedoui A, Lazar NA (2020) Bayesian empirical likelihood for ridge and lasso regressions. Comput Stat Data Anal 145:106917","journal-title":"Comput Stat Data Anal"},{"issue":"2","key":"3347_CR2","doi-asserted-by":"publisher","first-page":"219","DOI":"10.3390\/electronics9020219","volume":"9","author":"S Bhattacharya","year":"2020","unstructured":"Bhattacharya S, Kaluri R, Singh S, Alazab M, Tariq U et al (2020) A novel PCA-firefly based XGBoost classification model for intrusion detection in networks using GPU. Electronics 9(2):219","journal-title":"Electronics"},{"key":"3347_CR3","doi-asserted-by":"crossref","unstructured":"Bilge L, Dumitra\u015f T (2012) Before we knew it: an empirical study of zero-day attacks in the real world. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, pp 833\u2013844","DOI":"10.1145\/2382196.2382284"},{"key":"3347_CR4","doi-asserted-by":"crossref","unstructured":"Boonyakunakorn P, Nunti C, Yamaka W (2019) Forecasting of Thailand\u2019s rice exports price: based on ridge and lasso regression. In: Proceedings of the 2nd International Conference on Big Data Technologies, pp 354\u2013357","DOI":"10.1145\/3358528.3358547"},{"key":"3347_CR5","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/j.eswa.2018.08.002","volume":"115","author":"JA Carter","year":"2019","unstructured":"Carter JA, Long CS, Smith BP, Smith TL, Donati GL (2019) Combining elemental analysis of toenails and machine learning techniques as a non-invasive diagnostic tool for the robust classification of type-2 diabetes. Expert Syst Appl 115:245\u2013255","journal-title":"Expert Syst Appl"},{"key":"3347_CR6","unstructured":"Centers for Disease Control and Prevention et al (2017) National diabetes statistics report, 2017. Centers for Disease Control and Prevention, US Department of Health and Human Services, Atlanta, GA, p 20"},{"issue":"665\u20132016\u201345133","key":"3347_CR7","doi-asserted-by":"publisher","first-page":"51","DOI":"10.7160\/aol.2016.080405","volume":"8","author":"N Deepa","year":"2016","unstructured":"Deepa N, Ganesan K (2016) Aqua site classification using neural network models. AGRIS On-line Pap Econ Inform 8(665\u20132016\u201345133):51\u201358","journal-title":"AGRIS On-line Pap Econ Inform"},{"issue":"12","key":"3347_CR8","doi-asserted-by":"publisher","first-page":"1407","DOI":"10.1007\/s12046-016-0569-5","volume":"41","author":"N Deepa","year":"2016","unstructured":"Deepa N, Ganesan K (2016) Mahalanobis taguchi system based criteria selection tool for agriculture crops. S\u0101dhan\u0101 41(12):1407\u20131414","journal-title":"S\u0101dhan\u0101"},{"issue":"4","key":"3347_CR9","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.1007\/s00521-016-2749-y","volume":"30","author":"N Deepa","year":"2018","unstructured":"Deepa N, Ganesan K (2018) Multi-class classification using hybrid soft decision model for agriculture crop selection. Neural Comput Appl 30(4):1025\u20131038","journal-title":"Neural Comput Appl"},{"issue":"4","key":"3347_CR10","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.1007\/s00521-017-3154-x","volume":"31","author":"N Deepa","year":"2019","unstructured":"Deepa N, Ganesan K (2019) Decision-making tool for crop selection for agriculture development. Neural Comput Appl 31(4):1215\u20131225","journal-title":"Neural Comput Appl"},{"issue":"21","key":"3347_CR11","doi-asserted-by":"publisher","first-page":"10793","DOI":"10.1007\/s00500-018-3633-8","volume":"23","author":"N Deepa","year":"2019","unstructured":"Deepa N, Ganesan K (2019) Hybrid rough fuzzy soft classifier based multi-class classification model for agriculture crop selection. Soft Comput 23(21):10793\u201310809","journal-title":"Soft Comput"},{"key":"3347_CR12","doi-asserted-by":"publisher","first-page":"144777","DOI":"10.1109\/ACCESS.2019.2945129","volume":"7","author":"NL Fitriyani","year":"2019","unstructured":"Fitriyani NL, Syafrudin M, Alfian G, Rhee J (2019) Development of disease prediction model based on ensemble learning approach for diabetes and hypertension. IEEE Access 7:144777\u2013144789","journal-title":"IEEE Access"},{"key":"3347_CR13","unstructured":"Fonti V, Belitser E (2017) Feature selection using lasso. In: VU Amsterdam Research Paper in Business Analytics, pp 1\u201325"},{"issue":"2","key":"3347_CR14","first-page":"25","volume":"6","author":"TR Gadekallu","year":"2017","unstructured":"Gadekallu TR, Khare N (2017) Cuckoo search optimized reduction and fuzzy logic classifier for heart disease and diabetes prediction. Int J Fuzzy Syst Appl (IJFSA) 6(2):25\u201342","journal-title":"Int J Fuzzy Syst Appl (IJFSA)"},{"issue":"2","key":"3347_CR15","doi-asserted-by":"publisher","first-page":"274","DOI":"10.3390\/electronics9020274","volume":"9","author":"TR Gadekallu","year":"2020","unstructured":"Gadekallu TR, Khare N, Bhattacharya S, Singh S, Reddy Maddikunta PK, Ra IH, Alazab M (2020) Early detection of diabetic retinopathy using pca-firefly based deep learning model. Electronics 9(2):274","journal-title":"Electronics"},{"key":"3347_CR16","doi-asserted-by":"publisher","first-page":"82337","DOI":"10.1109\/ACCESS.2019.2923916","volume":"7","author":"C Iwendi","year":"2019","unstructured":"Iwendi C, Alqarni MA, Anajemba JH, Alfakeeh AS, Zhang Z, Bashir AK (2019) Robust navigational control of a two-wheeled self-balancing robot in a sensed environment. IEEE Access 7:82337\u201382348","journal-title":"IEEE Access"},{"key":"3347_CR17","doi-asserted-by":"publisher","first-page":"47258","DOI":"10.1109\/ACCESS.2018.2864111","volume":"6","author":"C Iwendi","year":"2018","unstructured":"Iwendi C, Uddin M, Ansere JA, Nkurunziza P, Anajemba JH, Bashir AK (2018) On detection of sybil attack in large-scale vanets using spider-monkey technique. IEEE Access 6:47258\u201347267","journal-title":"IEEE Access"},{"issue":"1","key":"3347_CR18","first-page":"193","volume":"28","author":"A Javaid","year":"2020","unstructured":"Javaid A, Ismail M, Ali MKM et al (2020) Efficient model selection of collector efficiency in solar dryer using hybrid of LASSO and robust regression. Pertanika J Sci Technol 28(1):193\u2013210","journal-title":"Pertanika J Sci Technol"},{"issue":"8","key":"3347_CR19","doi-asserted-by":"publisher","first-page":"4737","DOI":"10.1007\/s11276-018-1759-3","volume":"25","author":"X Jia","year":"2019","unstructured":"Jia X, He D, Kumar N, Choo KKR (2019) Authenticated key agreement scheme for fog-driven iot healthcare system. Wirel Netw 25(8):4737\u20134750","journal-title":"Wirel Netw"},{"key":"3347_CR20","unstructured":"Kaggle (2019) Diabetes detection. https:\/\/www.kaggle.com\/uciml\/pima-indians-diabetes-database. Accessed Mar 2019"},{"key":"3347_CR21","unstructured":"Kalimeris D, Kaplun G, Nakkiran P, Edelman B, Yang T, Barak B, Zhang H (2019) SGD on neural networks learns functions of increasing complexity. In: Advances in Neural Information Processing Systems, pp 3491\u20133501"},{"issue":"22","key":"3347_CR22","first-page":"8887","volume":"98","author":"G Kaur","year":"2014","unstructured":"Kaur G, Chhabra A (2014) Improved j48 classification algorithm for the prediction of diabetes. Int J Comput Appl 98(22):8887","journal-title":"Int J Comput Appl"},{"key":"3347_CR23","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.cmpb.2017.09.004","volume":"152","author":"M Maniruzzaman","year":"2017","unstructured":"Maniruzzaman M, Kumar N, Abedin MM, Islam MS, Suri HS, El-Baz AS, Suri JS (2017) Comparative approaches for classification of diabetes mellitus data: machine learning paradigm. Comput Methods Programs Biomed 152:23\u201334","journal-title":"Comput Methods Programs Biomed"},{"issue":"5","key":"3347_CR24","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1007\/s10916-018-0940-7","volume":"42","author":"M Maniruzzaman","year":"2018","unstructured":"Maniruzzaman M, Rahman MJ, Al-MehediHasan M, Suri HS, Abedin MM, El-Baz A, Suri JS (2018) Accurate diabetes risk stratification using machine learning: role of missing value and outliers. J Med Syst 42(5):92","journal-title":"J Med Syst"},{"key":"3347_CR25","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1016\/j.compeleceng.2018.07.041","volume":"77","author":"MW Moreira","year":"2019","unstructured":"Moreira MW, Rodrigues JJ, Furtado V, Kumar N, Korotaev VV (2019) Averaged one-dependence estimators on edge devices for smart pregnancy data analysis. Comput Electr Eng 77:435\u2013444","journal-title":"Comput Electr Eng"},{"key":"3347_CR26","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.inffus.2018.07.001","volume":"47","author":"MW Moreira","year":"2019","unstructured":"Moreira MW, Rodrigues JJ, Kumar N, Saleem K, Illin IV (2019) Postpartum depression prediction through pregnancy data analysis for emotion-aware smart systems. Inf Fusion 47:23\u201331","journal-title":"Inf Fusion"},{"key":"3347_CR27","doi-asserted-by":"crossref","unstructured":"Ogutu JO, Schulz-Streeck T, Piepho HP (2012) Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions. In: BMC proceedings, vol\u00a06. Springer, p S10","DOI":"10.1186\/1753-6561-6-S2-S10"},{"issue":"Supplement 1","key":"3347_CR28","doi-asserted-by":"publisher","first-page":"S13","DOI":"10.2337\/dc19-S002","volume":"42","author":"American Diabetes Association","year":"2019","unstructured":"American Diabetes Association (2019) 2. Classification and diagnosis of diabetes: standards of medical care in diabetes\u20142019. Diabetes Care 42(Supplement 1):S13\u2013S28","journal-title":"Diabetes Care"},{"issue":"4","key":"3347_CR29","doi-asserted-by":"publisher","first-page":"155014772091640","DOI":"10.1177\/1550147720916404","volume":"16","author":"H Patel","year":"2020","unstructured":"Patel H, Singh Rajput D, Thippa Reddy G, Iwendi C, Kashif Bashir A, Jo O (2020) A review on classification of imbalanced data for wireless sensor networks. Int J Distrib Sens Netw 16(4):1550147720916404","journal-title":"Int J Distrib Sens Netw"},{"key":"3347_CR30","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1016\/S2212-5671(16)30310-0","volume":"39","author":"JM Pereira","year":"2016","unstructured":"Pereira JM, Basto M, da Silva AF (2016) The logistic lasso and ridge regression in predicting corporate failure. Procedia Econ Finance 39:634\u2013641","journal-title":"Procedia Econ Finance"},{"key":"3347_CR31","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.jpdc.2020.02.010","volume":"142","author":"RM Priya","year":"2020","unstructured":"Priya RM, Bhattacharya S, Maddikunta PKR, Somayaji SRK, Lakshmanna K, Kaluri R, Hussien A, Gadekallu TR (2020) Load balancing of energy cloud using wind driven and firefly algorithms in internet of everything. J Parallel Distrib Comput 142:16\u201326","journal-title":"J Parallel Distrib Comput"},{"issue":"3","key":"3347_CR32","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1504\/IJBET.2018.094122","volume":"27","author":"GT Reddy","year":"2018","unstructured":"Reddy GT, Khare N (2018) Heart disease classification system using optimised fuzzy rule based algorithm. Int J Biomed Eng Technol 27(3):183\u2013202","journal-title":"Int J Biomed Eng Technol"},{"key":"3347_CR33","doi-asserted-by":"publisher","first-page":"54776","DOI":"10.1109\/ACCESS.2020.2980942","volume":"8","author":"GT Reddy","year":"2020","unstructured":"Reddy GT, Reddy MPK, Lakshmanna K, Kaluri R, Rajput DS, Srivastava G, Baker T (2020) Analysis of dimensionality reduction techniques on big data. IEEE Access 8:54776\u201354788","journal-title":"IEEE Access"},{"key":"3347_CR34","first-page":"1","volume":"13","author":"GT Reddy","year":"2019","unstructured":"Reddy GT, Reddy MPK, Lakshmanna K, Rajput DS, Kaluri R, Srivastava G (2019) Hybrid genetic algorithm and a fuzzy logic classifier for heart disease diagnosis. Evol Intell 13:1\u201312","journal-title":"Evol Intell"},{"key":"3347_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2020.04.004","author":"T Reddy","year":"2020","unstructured":"Reddy T, RM SP, Parimala M, Chowdhary CL, Hakak S, Khan WZ (2020) A deep neural networks based model for uninterrupted marine environment monitoring. Comput Commun. https:\/\/doi.org\/10.1016\/j.comcom.2020.04.004","journal-title":"Comput Commun"},{"key":"3347_CR36","doi-asserted-by":"publisher","first-page":"1068","DOI":"10.1016\/j.asoc.2018.09.038","volume":"73","author":"A Sharma","year":"2018","unstructured":"Sharma A (2018) Guided stochastic gradient descent algorithm for inconsistent datasets. Appl Soft Comput 73:1068\u20131080","journal-title":"Appl Soft Comput"},{"key":"3347_CR37","doi-asserted-by":"publisher","first-page":"1578","DOI":"10.1016\/j.procs.2018.05.122","volume":"132","author":"D Sisodia","year":"2018","unstructured":"Sisodia D, Sisodia DS (2018) Prediction of diabetes using classification algorithms. Procedia Comput Sci 132:1578\u20131585","journal-title":"Procedia Comput Sci"},{"key":"3347_CR38","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/j.ins.2015.03.073","volume":"316","author":"K Sopy\u0142a","year":"2015","unstructured":"Sopy\u0142a K, Drozda P (2015) Stochastic gradient descent with Barzilai\u2013Borwein update step for SVM. Inf Sci 316:218\u2013233","journal-title":"Inf Sci"},{"issue":"2","key":"3347_CR39","doi-asserted-by":"publisher","first-page":"20","DOI":"10.3390\/proteomes6020020","volume":"6","author":"A Suppers","year":"2018","unstructured":"Suppers A, Gool AJv, Wessels HJ (2018) Integrated chemometrics and statistics to drive successful proteomics biomarker discovery. Proteomes 6(2):20","journal-title":"Proteomes"},{"key":"3347_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2020.02.065","author":"Z Uddin","year":"2020","unstructured":"Uddin Z, Altaf M, Bilal M, Nkenyereye L, Bashir AK (2020) Amateur drones detection: a machine learning approach utilizing the acoustic signals in the presence of strong interference. Comput Commun. https:\/\/doi.org\/10.1016\/j.comcom.2020.02.065","journal-title":"Comput Commun"},{"key":"3347_CR41","doi-asserted-by":"publisher","first-page":"107138","DOI":"10.1016\/j.comnet.2020.107138","volume":"171","author":"D Vasan","year":"2020","unstructured":"Vasan D, Alazab M, Wassan S, Naeem H, Safaei B, Zheng Q (2020) IMCFN: image-based malware classification using fine-tuned convolutional neural network architecture. Comput Netw 171:107138","journal-title":"Comput Netw"},{"key":"3347_CR42","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1016\/j.neunet.2017.06.003","volume":"93","author":"L Wang","year":"2017","unstructured":"Wang L, Yang Y, Min R, Chakradhar S (2017) Accelerating deep neural network training with inconsistent stochastic gradient descent. Neural Netw 93:219\u2013229","journal-title":"Neural Netw"},{"key":"3347_CR43","unstructured":"Widrow B (1960) An adaptive ADALINE neuron using chemical. Stanford University"},{"issue":"11","key":"3347_CR44","doi-asserted-by":"publisher","first-page":"1850036","DOI":"10.1142\/S0218001418500362","volume":"32","author":"X Xing","year":"2018","unstructured":"Xing X, Wen D, Chang HC, Chen LF, Yuan ZH (2018) Highway deformation monitoring based on an integrated crinsar algorithmsimulation and real data validation. Int J Pattern Recognit Artif Intell 32(11):1850036","journal-title":"Int J Pattern Recognit Artif Intell"},{"issue":"4","key":"3347_CR45","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1109\/TNNLS.2016.2641475","volume":"29","author":"X Zeng","year":"2017","unstructured":"Zeng X, Peng H, Zhou F (2017) A regularized SNPOM for stable parameter estimation of RBF-AR (X) model. IEEE Trans Neural Netw Learn Syst 29(4):779\u2013791","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"3","key":"3347_CR46","doi-asserted-by":"publisher","first-page":"913497","DOI":"10.1155\/2013\/913497","volume":"9","author":"J Zhang","year":"2013","unstructured":"Zhang J, Yang K, Xiang L, Luo Y, Xiong B, Tang Q (2013) A self-adaptive regression-based multivariate data compression scheme with error bound in wireless sensor networks. Int J Distrib Sensor Netw 9(3):913497","journal-title":"Int J Distrib Sensor Netw"},{"key":"3347_CR47","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.ijmedinf.2016.09.014","volume":"97","author":"T Zheng","year":"2017","unstructured":"Zheng T, Xie W, Xu L, He X, Zhang Y, You M, Yang G, Chen Y (2017) A machine learning-based framework to identify type 2 diabetes through electronic health records. Int J Med Inform 97:120\u2013127","journal-title":"Int J Med Inform"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-020-03347-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-020-03347-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-020-03347-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,29]],"date-time":"2021-05-29T23:21:55Z","timestamp":1622330515000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-020-03347-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,30]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["3347"],"URL":"https:\/\/doi.org\/10.1007\/s11227-020-03347-2","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,30]]},"assertion":[{"value":"30 May 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}