{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T18:04:04Z","timestamp":1742925844474,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031213847"},{"type":"electronic","value":"9783031213854"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-21385-4_26","type":"book-chapter","created":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T05:03:52Z","timestamp":1670907832000},"page":"306-320","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An 8-Layered MLP Network for Detection of Cardiac Arrest at an Early Stage of Disease"],"prefix":"10.1007","author":[{"given":"N.","family":"Venkata Maha Lakshmi","sequence":"first","affiliation":[]},{"given":"Ranjeet Kumar","family":"Rout","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,14]]},"reference":[{"key":"26_CR1","doi-asserted-by":"publisher","unstructured":"Kumar, N.K., Sindhu, G.S., Prashanthi, D.K., Sulthana, A.S.: Analysis and prediction of cardio vascular disease using machine learning classifiers. In: 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) (2020). https:\/\/doi.org\/10.1109\/icaccs48705.2020.9074183","DOI":"10.1109\/icaccs48705.2020.9074183"},{"key":"26_CR2","doi-asserted-by":"publisher","unstructured":"Motarwar, P., Duraphe, A., Suganya, G., Premalatha, M.: Cognitive approach for heart disease prediction using machine learning. In: 2020 International Conference on Emerging Trends in Information Technology and Engineering (IC-ETITE) (2020). https:\/\/doi.org\/10.1109\/ic-etite47903.2020.242","DOI":"10.1109\/ic-etite47903.2020.242"},{"key":"26_CR3","series-title":"Lecture Notes in Electrical Engineering","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1007\/978-981-15-5262-5_67","volume-title":"Advances in Electrical Control and Signal Systems","author":"S Barik","year":"2020","unstructured":"Barik, S., Mohanty, S., Rout, D., Mohanty, S., Patra, A.K., Mishra, A.K.: Heart disease prediction using machine learning techniques. In: Pradhan, G., Morris, S., Nayak, N. (eds.) Advances in Electrical Control and Signal Systems. LNEE, vol. 665, pp. 879\u2013888. Springer, Singapore (2020). https:\/\/doi.org\/10.1007\/978-981-15-5262-5_67"},{"key":"26_CR4","doi-asserted-by":"publisher","first-page":"3213","DOI":"10.1016\/j.matpr.2020.09.078","volume":"37","author":"M Diwakar","year":"2021","unstructured":"Diwakar, M., Tripathi, A., Joshi, K., Memoria, M., Singh, P., Kumar, N.: Latest trends on heart disease prediction using machine learning and image fusion. Mater. Today: Proc. 37, 3213\u20133218 (2021). https:\/\/doi.org\/10.1016\/j.matpr.2020.09.078","journal-title":"Mater. Today: Proc."},{"key":"26_CR5","doi-asserted-by":"publisher","unstructured":"Saw, M., Saxena, T., Kaithwas, S., Yadav, R., Lal, N.: Estimation of prediction for getting heart disease using logistic regression model of machine learning. In: 2020 International Conference on Computer Communication and Informatics (ICCCI) (2020). https:\/\/doi.org\/10.1109\/iccci48352.2020.9104210","DOI":"10.1109\/iccci48352.2020.9104210"},{"key":"26_CR6","doi-asserted-by":"publisher","first-page":"25394","DOI":"10.1109\/access.2021.3057693","volume":"9","author":"M Wang","year":"2021","unstructured":"Wang, M., Yao, X., Chen, Y.: An imbalanced-data processing algorithm for the prediction of heart attack in stroke patients. IEEE Access 9, 25394\u201325404 (2021). https:\/\/doi.org\/10.1109\/access.2021.3057693","journal-title":"IEEE Access"},{"issue":"3","key":"26_CR7","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1007\/s12553-019-00396-3","volume":"10","author":"J Nourmohammadi-Khiarak","year":"2019","unstructured":"Nourmohammadi-Khiarak, J., Feizi-Derakhshi, M.-R., Behrouzi, K., Mazaheri, S., Zamani-Harghalani, Y., Tayebi, R.M.: New hybrid method for heart disease diagnosis utilizing optimization algorithm in feature selection. Heal. Technol. 10(3), 667\u2013678 (2019). https:\/\/doi.org\/10.1007\/s12553-019-00396-3","journal-title":"Heal. Technol."},{"issue":"1","key":"26_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-019-0244-x","volume":"6","author":"FI Alarsan","year":"2019","unstructured":"Alarsan, F.I., Younes, M.: Analysis and classification of heart diseases using heartbeat features and machine learning algorithms. J. Big Data 6(1), 1\u201315 (2019). https:\/\/doi.org\/10.1186\/s40537-019-0244-x","journal-title":"J. Big Data"},{"issue":"5","key":"26_CR9","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1016\/0002-9149(89)90524-9","volume":"64","author":"R Detrano","year":"1989","unstructured":"Detrano, R., et al.: International application of a new probability algorithm for the diagnosis of coronary artery disease. Am. J. Cardiol. 64(5), 304\u2013310 (1989)","journal-title":"Am. J. Cardiol."},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Gudadhe, M., Wankhade, K., Dongre, S.: Decision support system for heart disease based on support vector machine and artificial neural network. In: Proceedings of International Conference on Computer and Communication Technology (ICCCT), pp. 741\u2013745 (2010)","DOI":"10.1109\/ICCCT.2010.5640377"},{"issue":"1\u20132","key":"26_CR11","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.eswa.2007.06.004","volume":"35","author":"H Kahramanli","year":"2008","unstructured":"Kahramanli, H., Allahverdi, N.: Design of a hybrid system for the diabetes and heart diseases. Expert Syst. Appl. 35(1\u20132), 82\u201389 (2008)","journal-title":"Expert Syst. Appl."},{"issue":"4","key":"26_CR12","doi-asserted-by":"publisher","first-page":"7675","DOI":"10.1016\/j.eswa.2008.09.013","volume":"36","author":"R Das","year":"2009","unstructured":"Das, R., Turkoglu, I., Sengur, A.: \u2018Effective diagnosis of heart disease through neural networks ensembles.\u2019 Expert Syst. Appl. 36(4), 7675\u20137680 (2009)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"26_CR13","first-page":"4","volume":"13","author":"MA Jabbar","year":"2013","unstructured":"Jabbar, M.A., Deekshatulu, B., Chandra, P.: Classification of heart disease using artificial neural network and feature subset selection. Glob. J. Comput. Sci. Technol. Neural Artif. Intell. 13(3), 4\u20138 (2013)","journal-title":"Glob. J. Comput. Sci. Technol. Neural Artif. Intell."},{"key":"26_CR14","doi-asserted-by":"crossref","unstructured":"Palaniappan, S., Awang, R.: Intelligent heart disease prediction system using data mining techniques. In: Proceedings of IEEE\/ACS International Conference on Computer Systems and Applications, pp. 108\u2013115 (2008)","DOI":"10.1109\/AICCSA.2008.4493524"},{"key":"26_CR15","unstructured":"Heart Disease Dataset Link. https:\/\/www.kaggle.com\/cherngs\/heart-disease-cleveland-uci"}],"container-title":["Communications in Computer and Information Science","Artificial Intelligence and Data Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-21385-4_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T15:27:11Z","timestamp":1691594831000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-21385-4_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031213847","9783031213854"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-21385-4_26","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"14 December 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICAIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence and Data Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hyderabad","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icaids2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icaids.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"195","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"22% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}