{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T20:48:09Z","timestamp":1769114889012,"version":"3.49.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T00:00:00Z","timestamp":1657497600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T00:00:00Z","timestamp":1657497600000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,11]]},"DOI":"10.1007\/s00521-022-07527-4","type":"journal-article","created":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T10:04:34Z","timestamp":1657620274000},"page":"19877-19893","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["An intelligent disease prediction and monitoring system using feature selection, multi-neural network and fuzzy rules"],"prefix":"10.1007","volume":"34","author":[{"given":"V.","family":"Elizabeth Jesi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shabnam Mohamed","family":"Aslam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,11]]},"reference":[{"issue":"4","key":"7527_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-016-0432-6","volume":"40","author":"GB Berikol","year":"2016","unstructured":"Berikol GB, Yildiz O, \u00d6zcan IT (2016) Diagnosis of acute coronary syndrome with a support vector machine. J Med Syst 40(4):1\u20138","journal-title":"J Med Syst"},{"issue":"1","key":"7527_CR2","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.compeleceng.2011.09.001","volume":"38","author":"O Er","year":"2012","unstructured":"Er O, Tanrikulu AC, Abakay A, Temurtas F (2012) An approach based on probabilistic neural network for diagnosis of mesotheliomas disease. Comput Electr Eng 38(1):75\u201381","journal-title":"Comput Electr Eng"},{"key":"7527_CR3","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Proceedings of advances in neural information processing systems, pp 1097\u20131105"},{"key":"7527_CR4","unstructured":"Zhang X, Zhao J, LeCun Y (2015) Character-level convolutional networks for text classification. In: Proceedings of advances in neural information processing systems, pp 649\u2013657"},{"issue":"5","key":"7527_CR5","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1109\/TSMCB.2003.816922","volume":"33","author":"ML Raymer","year":"2003","unstructured":"Raymer ML, Doom TE, Kuhn LA, Punch WF (2003) \"Knowledge discovery in medical and biological datasets using a hybrid Bayes classifier\/evolutionary algorithm. IEEE Trans Syst Man Cybern Part B (Cybern) 33(5):802\u2013813. https:\/\/doi.org\/10.1109\/TSMCB.2003.816922","journal-title":"IEEE Trans Syst Man Cybern Part B (Cybern)"},{"issue":"4","key":"7527_CR6","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1109\/TITB.2011.2175938","volume":"16","author":"EE Tripoliti","year":"2012","unstructured":"Tripoliti EE, Fotiadis DI, Manis G (2012) Automated diagnosis of diseases based on classification: dynamic determination of the number of trees in random forests algorithm. IEEE Trans Inf Technol Biomed 16(4):615\u2013622. https:\/\/doi.org\/10.1109\/TITB.2011.2175938","journal-title":"IEEE Trans Inf Technol Biomed"},{"issue":"16","key":"7527_CR7","doi-asserted-by":"publisher","first-page":"12697","DOI":"10.1016\/j.eswa.2012.05.014","volume":"39","author":"A Tsimpiris","year":"2012","unstructured":"Tsimpiris A, Vlachos I, Kugiumtzis D (2012) Nearest neighbor estimate of conditional mutual information in feature selection. Expert Syst Appl 39(16):12697\u201312708","journal-title":"Expert Syst Appl"},{"key":"7527_CR8","first-page":"1","volume":"271","author":"S Ganapathy","year":"2013","unstructured":"Ganapathy S, Kulothungan K, Muthurajkumar S, Yogesh P, Vijalakshmi M, Kannan A (2013) Intelligent feature selection and classification techniques for effective intrusion detection: a survey. Comput Intell Neurosci 271:1\u201316","journal-title":"Comput Intell Neurosci"},{"key":"7527_CR9","doi-asserted-by":"publisher","unstructured":"Narasimhan B, Malathi A (2014) A fuzzy logic system with attribute ranking technique for risk-level classification of CAHD in female diabetic patients, In: 2014 International conference on intelligent computing applications, Coimbatore, pp 179\u2013183. https:\/\/doi.org\/10.1109\/ICICA.2014.46","DOI":"10.1109\/ICICA.2014.46"},{"issue":"2","key":"7527_CR10","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/s12046-014-0236-7","volume":"39","author":"S Ganapathy","year":"2014","unstructured":"Ganapathy S, Sethukkarasi R, Yogesh P, Vijayakumar P, Kannan A (2014) An intelligent temporal pattern classification system using fuzzy temporal rules and particle swarm optimization. Sadhana 39(2):283\u2013302","journal-title":"Sadhana"},{"issue":"4","key":"7527_CR11","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1109\/TCBB.2014.2315996","volume":"11","author":"Yu Zhiwen","year":"2014","unstructured":"Zhiwen Yu, Chen H, You J, Wong H-S, Liu J, Li Le, Han G (2014) Double selection based semi-supervised clustering ensemble for tumor clustering from gene expression profiles. IEEE\/ACM Trans Comput Biol Bioinf 11(4):727\u2013740","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"key":"7527_CR12","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/j.snb.2014.09.115","volume":"217","author":"XW Rosalind","year":"2015","unstructured":"Rosalind XW, Lizier JT, Berna AZ, Bravo FG, Trowell SC (2015) Human breath-print identification by E-nose, using information-theoretic feature selection prior to classification. Sens Actuat B Chem 217:165\u2013174","journal-title":"Sens Actuat B Chem"},{"key":"7527_CR13","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.compbiomed.2015.06.021","volume":"64","author":"TT Erguzel","year":"2015","unstructured":"Erguzel TT, Tas C, Cebi M (2015) A wrapper-based approach for feature selection and classification of major depressive disorder\u2013bipolar disorders. Comput Biol Med 64:127\u2013137","journal-title":"Comput Biol Med"},{"key":"7527_CR14","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.asoc.2015.01.035","volume":"30","author":"V Bol\u00f3n-Canedo","year":"2015","unstructured":"Bol\u00f3n-Canedo V, S\u00e1nchez-Maro\u00f1o N, Alonso-Betanzos A (2015) Distributed feature selection: an application to microarray data classification. Appl Soft Comput 30:136\u2013150","journal-title":"Appl Soft Comput"},{"key":"7527_CR15","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.cmpb.2016.01.020","volume":"127","author":"S Nalband","year":"2016","unstructured":"Nalband S, Sundar A, Amalin Prince A, Agarwal A (2016) Feature selection and classification methodology for the detection of knee-joint disorders. Comput Methods Progr Biomed 127:94\u2013104","journal-title":"Comput Methods Progr Biomed"},{"issue":"2","key":"7527_CR16","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.aci.2014.03.002","volume":"12","author":"S Sasikala","year":"2016","unstructured":"Sasikala S, Appavu alias Balamurugan S, Geetha S (2016) Multi filtration feature selection (MFFS) to improve discriminatory ability in clinical data set. Appl Comput Inform 12(2):117\u2013127","journal-title":"Appl Comput Inform"},{"issue":"6","key":"7527_CR17","doi-asserted-by":"publisher","first-page":"1327","DOI":"10.1109\/TCBB.2016.2570216","volume":"14","author":"A Akkasi","year":"2017","unstructured":"Akkasi A, Varo\u011flu E (2017) Improving biochemical named entity recognition using PSO classifier selection and bayesian combination methods. IEEE\/ACM Trans Comput Biol Bioinform 14(6):1327\u20131338. https:\/\/doi.org\/10.1109\/TCBB.2016.2570216","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"issue":"4","key":"7527_CR18","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1109\/TMSCS.2017.2710194","volume":"3","author":"H Yin","year":"2017","unstructured":"Yin H, Jha NK (2017) A health decision support system for disease diagnosis based on wearable medical sensors and machine learning ensembles. IEEE Trans Multi-Scale Comput Syst 3(4):228\u2013241","journal-title":"IEEE Trans Multi-Scale Comput Syst"},{"key":"7527_CR19","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.jbi.2018.09.011","volume":"87","author":"Z Zhang","year":"2018","unstructured":"Zhang Z, Ze Hu, Yang H, Zhu R, Zuo D (2018) Factorization machines and deep views-based co-training for improving answer quality prediction in online health expert question-answering services. J Biomed Inform 87:21\u201336","journal-title":"J Biomed Inform"},{"key":"7527_CR20","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.jbi.2018.10.002","volume":"87","author":"J Chu","year":"2018","unstructured":"Chu J, Dong W, He K, Duan H, Huang Z (2018) Using neural attention networks to detect adverse medical events from electronic health records. J Biomed Inform 87:118\u2013130","journal-title":"J Biomed Inform"},{"key":"7527_CR21","doi-asserted-by":"publisher","unstructured":"Dey SK, Hossain A, Rahman MM (2018) Implementation of a web application to predict diabetes disease: an approach using machine learning algorithm. In: 2018 21st international conference of computer and information technology (ICCIT), Dhaka, Bangladesh, pp 1\u20135. https:\/\/doi.org\/10.1109\/ICCITECHN.2018.8631968","DOI":"10.1109\/ICCITECHN.2018.8631968"},{"issue":"2","key":"7527_CR22","doi-asserted-by":"publisher","first-page":"451","DOI":"10.18576\/amis\/120220","volume":"12","author":"TJ Vijay Kumar","year":"2018","unstructured":"Vijay Kumar TJ, Lavanya N, Khanna Nehemiah H, Ganapathy S, Kannan A (2018) Identification and classification of pulmonary nodule in lung modality using digital computer. Appl Math Inf Sci 12(2):451\u2013459","journal-title":"Appl Math Inf Sci"},{"key":"7527_CR23","doi-asserted-by":"publisher","unstructured":"Woldemichael FG, Menaria S (2018) Prediction of diabetes using data mining techniques. In: 2018 2nd international conference on trends in electronics and informatics (ICOEI), Tirunelveli, pp 414\u2013418. https:\/\/doi.org\/10.1109\/ICOEI.2018.8553959","DOI":"10.1109\/ICOEI.2018.8553959"},{"issue":"03","key":"7527_CR24","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/s40009-018-0732-0","volume":"42","author":"U Kanimozhi","year":"2019","unstructured":"Kanimozhi U, Ganapathy S, Manjula D, Kannan A (2019) An intelligent risk prediction system for breast cancer using fuzzy temporal rules. Natl Acad Sci Lett 42(03):227\u2013232","journal-title":"Natl Acad Sci Lett"},{"issue":"5","key":"7527_CR25","doi-asserted-by":"publisher","first-page":"1085","DOI":"10.1109\/TFUZZ.2019.2892363","volume":"27","author":"F Jim\u00e9nez","year":"2019","unstructured":"Jim\u00e9nez F, Mart\u00ednez C, Marzano E, Palma JT, S\u00e1nchez G, Sciavicco G (2019) Multiobjective evolutionary feature selection for fuzzy classification. IEEE Trans Fuzzy Syst 27(5):1085\u20131099","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"7527_CR26","doi-asserted-by":"publisher","first-page":"54007","DOI":"10.1109\/ACCESS.2019.2909969","volume":"7","author":"L Ali","year":"2019","unstructured":"Ali L, Niamat A, Khan JA, Golilarz NA, Xingzhong X, Noor A, Nour R, Bukhari SAC (2019) An optimized stacked support vector machines based expert system for the effective prediction of heart failure. IEEE Access 7:54007\u201354014","journal-title":"IEEE Access"},{"key":"7527_CR27","doi-asserted-by":"publisher","first-page":"105740","DOI":"10.1016\/j.asoc.2019.105740","volume":"84","author":"P P\u0142awiak","year":"2019","unstructured":"P\u0142awiak P, Abdar M, Rajendra Achary U (2019) Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring. Appl Soft Comput 84:105740","journal-title":"Appl Soft Comput"},{"issue":"2","key":"7527_CR28","first-page":"133","volume":"34","author":"P Li","year":"2019","unstructured":"Li P, Yuan Z, Kai WT, Lu YD (2019) Medical knowledge extraction and analysis from electronic medical records using deep learning. Chin Med Sci J 34(2):133\u2013139","journal-title":"Chin Med Sci J"},{"key":"7527_CR29","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.neucom.2019.04.038","volume":"356","author":"B Zhang","year":"2019","unstructured":"Zhang B, Xu X, Li X, Chen X, Ye Y, Wang Z (2019) Sentiment analysis through critic learning for optimizing convolutional neural networks with rules. Neurocomputing 356:21\u201330","journal-title":"Neurocomputing"},{"issue":"10","key":"7527_CR30","doi-asserted-by":"publisher","first-page":"105162","DOI":"10.1016\/j.jstrokecerebrovasdis.2020.105162","volume":"29","author":"MS Sirsat","year":"2020","unstructured":"Sirsat MS, Ferm\u00e9 E, C\u00e2mara J (2020) Machine learning for brain stroke: a review. J Stroke Cerebrovasc Dis 29(10):105162","journal-title":"J Stroke Cerebrovasc Dis"},{"key":"7527_CR31","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.comcom.2020.05.035","volume":"160","author":"H-Y Hsu","year":"2020","unstructured":"Hsu H-Y, Srivastava G, Hsin-Te Wu, Chen M-Y (2020) Remaining useful life prediction based on state assessment using edge computing on deep learning. Comput Commun 160:91\u2013100","journal-title":"Comput Commun"},{"issue":"3","key":"7527_CR32","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1049\/iet-sen.2019.0261","volume":"14","author":"BS Raja","year":"2020","unstructured":"Raja BS, Asghar S (2020) Using health data repositories for developing clinical system software: a multi-objective fuzzy genetic approach. IET Softw 14(3):254\u2013264","journal-title":"IET Softw"},{"key":"7527_CR33","doi-asserted-by":"publisher","first-page":"135784","DOI":"10.1109\/ACCESS.2020.3007561","volume":"8","author":"SS Sarmah","year":"2020","unstructured":"Sarmah SS (2020) An efficient IoT-based patient monitoring and heart disease prediction system using deep learning modified neural network. IEEE Access 8:135784\u2013135797","journal-title":"IEEE Access"},{"key":"7527_CR34","doi-asserted-by":"publisher","first-page":"150489","DOI":"10.1109\/ACCESS.2020.3016782","volume":"8","author":"J Latif","year":"2020","unstructured":"Latif J, Xiao C, Tu S, Rehman SU, Imran A, Bilal A (2020) Implementation and use of disease diagnosis systems for electronic medical records based on machine learning: a complete review. IEEE Access 8:150489\u2013150513","journal-title":"IEEE Access"},{"key":"7527_CR35","doi-asserted-by":"publisher","first-page":"103488","DOI":"10.1016\/j.jbi.2020.103488","volume":"108","author":"G Alfattni","year":"2020","unstructured":"Alfattni G, Peek N, Nenadi G (2020) Extraction of temporal relations from clinical free text: a systematic review of current approaches. J Biomed Inform 108:103488","journal-title":"J Biomed Inform"},{"key":"7527_CR36","doi-asserted-by":"publisher","first-page":"105949","DOI":"10.1016\/j.knosys.2020.105949","volume":"198","author":"ME Basiri","year":"2020","unstructured":"Basiri ME, Abdar M, AkifCifci M, Nemati S, RajendraAcharya U (2020) A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques. Knowl-Based Syst 198:105949","journal-title":"Knowl-Based Syst"},{"key":"7527_CR37","doi-asserted-by":"publisher","first-page":"103609","DOI":"10.1016\/j.jbi.2020.103609","volume":"112","author":"S Gajendran","year":"2020","unstructured":"Gajendran S, Manjula D, Sugumaran V (2020) Character level and word level embedding with bidirectional LSTM-dynamic recurrent neural network for biomedical named entity recognition from literature. J Biomed Inform 112:103609","journal-title":"J Biomed Inform"},{"key":"7527_CR38","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.future.2019.10.043","volume":"104","author":"S Tuli","year":"2020","unstructured":"Tuli S, Basumatary N, Gill SS, Kahani M, Arya RC, Wander GS, Buyya R (2020) HealthFog: an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and fog computing environments. Fut Gen Comput Syst 104:187\u2013200","journal-title":"Fut Gen Comput Syst"},{"key":"7527_CR39","doi-asserted-by":"publisher","first-page":"107562","DOI":"10.1109\/ACCESS.2020.3001149","volume":"8","author":"JP Li","year":"2020","unstructured":"Li JP, Haq AU, Din SU, Khan J, Khan A, Saboor A (2020) Heart disease identification method using machine learning classification in e-healthcare. IEEE Access 8:107562\u2013107582","journal-title":"IEEE Access"},{"key":"7527_CR40","first-page":"1531","volume":"5","author":"F Fleuret","year":"2004","unstructured":"Fleuret F (2004) Fast binary feature selection with conditional mutual information. J Mach Learn Res 5:1531\u20131555","journal-title":"J Mach Learn Res"},{"key":"7527_CR41","doi-asserted-by":"publisher","first-page":"1292","DOI":"10.1109\/ACCESS.2017.2778268","volume":"6","author":"R Alzubi","year":"2018","unstructured":"Alzubi R, Ramzan N, Alzoubi H, Amira A (2018) A hybrid feature selection method for complex diseases SNPs. IEEE Access 6:1292\u20131301","journal-title":"IEEE Access"},{"key":"7527_CR42","volume-title":"UCI repository of machine learning databases, (machine-readable data repository)","author":"PM Murphy","year":"1995","unstructured":"Murphy PM, Aha DW (1995) UCI repository of machine learning databases, (machine-readable data repository). University of California, Irvine"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-07527-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-022-07527-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-022-07527-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,20]],"date-time":"2022-10-20T20:50:19Z","timestamp":1666299019000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-022-07527-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,11]]},"references-count":42,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2022,11]]}},"alternative-id":["7527"],"URL":"https:\/\/doi.org\/10.1007\/s00521-022-07527-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,11]]},"assertion":[{"value":"3 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 June 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 July 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The author declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}