{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T20:17:24Z","timestamp":1743020244603,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031382031"},{"type":"electronic","value":"9783031382048"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-38204-8_8","type":"book-chapter","created":{"date-parts":[[2023,7,29]],"date-time":"2023-07-29T03:18:08Z","timestamp":1690600688000},"page":"91-100","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Recommendation of\u00a0Medical Exams to\u00a0Support Clinical Diagnosis Based on\u00a0Patient\u2019s Symptoms"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8736-7443","authenticated-orcid":false,"given":"Cristiana","family":"Neto","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2326-2153","authenticated-orcid":false,"given":"Diana","family":"Ferreira","sequence":"additional","affiliation":[]},{"given":"Hugo","family":"Cunha","sequence":"additional","affiliation":[]},{"given":"Maria","family":"Pires","sequence":"additional","affiliation":[]},{"given":"Susana","family":"Marques","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2988-196X","authenticated-orcid":false,"given":"Regina","family":"Sousa","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4121-6169","authenticated-orcid":false,"given":"Jos\u00e9","family":"Machado","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,30]]},"reference":[{"key":"8_CR1","unstructured":"Naive Bayes. https:\/\/scikit-learn.org\/stable\/modules\/naive_bayes.html"},{"key":"8_CR2","unstructured":"Nearest neighbors. https:\/\/scikit-learn.org\/stable\/modules\/neighbors.html#neighbors"},{"key":"8_CR3","unstructured":"Onevsrestclassifier. https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.multiclass.OneVsRestClassifier.html"},{"key":"8_CR4","unstructured":"SVM. https:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.svm.SVC.html"},{"issue":"6","key":"8_CR5","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TKDE.2005.99","volume":"17","author":"G Adomavicius","year":"2005","unstructured":"Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734\u2013749 (2005)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"8_CR6","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/978-3-319-50478-0_20","volume-title":"Machine Learning for Health Informatics","author":"A Calero Valdez","year":"2016","unstructured":"Calero Valdez, A., Ziefle, M., Verbert, K., Felfernig, A., Holzinger, A.: Recommender systems for health informatics: state-of-the-art and future perspectives. In: Holzinger, A. (ed.) Machine Learning for Health Informatics. LNCS (LNAI), vol. 9605, pp. 391\u2013414. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-50478-0_20"},{"key":"8_CR7","doi-asserted-by":"crossref","unstructured":"Chow, T.W.S., Cho, D.S.Y.: Neural Networks and Computing: Learning Algorithms and Applications, vol. 7. World Scientific (2007)","DOI":"10.1142\/p487"},{"issue":"16","key":"8_CR8","doi-asserted-by":"publisher","first-page":"8043","DOI":"10.3390\/app12168043","volume":"12","author":"D Ferreira","year":"2022","unstructured":"Ferreira, D., Neto, C., Lopes, J., Duarte, J., Abelha, A., Machado, J.: Predicting the survival of primary biliary cholangitis patients. Appl. Sci. 12(16), 8043 (2022)","journal-title":"Appl. Sci."},{"issue":"1","key":"8_CR9","first-page":"96","volume":"2","author":"SB Maind","year":"2014","unstructured":"Maind, S.B., Wankar, P., et al.: Research paper on basic of artificial neural network. Int. J. Recent Innov. Trends Comput. Commun. 2(1), 96\u2013100 (2014)","journal-title":"Int. J. Recent Innov. Trends Comput. Commun."},{"issue":"1","key":"8_CR10","doi-asserted-by":"publisher","first-page":"13","DOI":"10.15171\/ijbsm.2016.04","volume":"1","author":"M Nasiri","year":"2016","unstructured":"Nasiri, M., Minaei, B., Kiani, A.: Dynamic recommendation: disease prediction and prevention using recommender system. Int. J. Basic Sci. Med. 1(1), 13\u201317 (2016)","journal-title":"Int. J. Basic Sci. Med."},{"issue":"12","key":"8_CR11","doi-asserted-by":"publisher","first-page":"1163","DOI":"10.3390\/e21121163","volume":"21","author":"C Neto","year":"2019","unstructured":"Neto, C., Brito, M., Lopes, V., Peixoto, H., Abelha, A., Machado, J.: Application of data mining for the prediction of mortality and occurrence of complications for gastric cancer patients. Entropy 21(12), 1163 (2019)","journal-title":"Entropy"},{"key":"8_CR12","doi-asserted-by":"publisher","first-page":"1104","DOI":"10.1016\/j.procs.2017.11.141","volume":"121","author":"C Neto","year":"2017","unstructured":"Neto, C., Peixoto, H., Abelha, V., Abelha, A., Machado, J.: Knowledge discovery from surgical waiting lists. Procedia Comput. Sci. 121, 1104\u20131111 (2017)","journal-title":"Procedia Comput. Sci."},{"key":"8_CR13","unstructured":"Patil, P.: Disease symptom prediction (2020). https:\/\/www.kaggle.com\/itachi9604\/disease-symptom-description-dataset"},{"key":"8_CR14","unstructured":"Patil, P.: Disease symptom prediction (2020). https:\/\/www.kaggle.com\/datasets\/itachi9604\/disease-symptom-description-dataset"},{"key":"8_CR15","doi-asserted-by":"crossref","unstructured":"Stark, B., Knahl, C., Aydin, M., Elish, K.: A literature review on medicine recommender systems. Int. J. Adv. Comput. Sci. Appl. 10(8) (2019)","DOI":"10.14569\/IJACSA.2019.0100802"},{"issue":"1","key":"8_CR16","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s10844-020-00633-6","volume":"57","author":"TNT Tran","year":"2021","unstructured":"Tran, T.N.T., Felfernig, A., Trattner, C., Holzinger, A.: Recommender systems in the healthcare domain: state-of-the-art and research issues. J. Intell. Inf. Syst. 57(1), 171\u2013201 (2021)","journal-title":"J. Intell. Inf. Syst."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-38204-8_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,29]],"date-time":"2023-07-29T03:19:30Z","timestamp":1690600770000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-38204-8_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031382031","9783031382048"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-38204-8_8","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"30 July 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AISCOVID","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Braga","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiscovid2022","order":10,"name":"conference_id","label":"Conference ID","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":"Confy +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21","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":"8","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":"38% - 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":"3","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":"3","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)"}}]}}