{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T10:29:20Z","timestamp":1743157760421,"version":"3.40.3"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031772986"},{"type":"electronic","value":"9783031772993"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-77299-3_4","type":"book-chapter","created":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T13:10:20Z","timestamp":1735650620000},"page":"32-42","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Patient Length of\u00a0Stay Using Machine Learning Models"],"prefix":"10.1007","author":[{"given":"Omar","family":"Khaled","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mostafa","family":"Tarek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaimaa","family":"Salah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Ezz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Omar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed F.","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,1]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"53","DOI":"10.20286\/hpr-010251","volume":"1","author":"S Aghajani","year":"2016","unstructured":"Aghajani, S., Kargari, M.: Determining factors influencing length of stay and predicting length of stay using data mining in the general surgery department. Hosp. Pract. Res. 1, 53\u201358 (2016)","journal-title":"Hosp. Pract. Res."},{"doi-asserted-by":"crossref","unstructured":"Chuang, M.T., Hu, Y.H., Tsai, C.F., Lo, C.L., Lin, W.C.: The identification of prolonged length of stay for surgery patients. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, pp. 3000\u20133003 (2016)","key":"4_CR2","DOI":"10.1109\/SMC.2015.522"},{"doi-asserted-by":"crossref","unstructured":"Cho, H.N., et al.: Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients: machine learning model development and evaluation (2023)","key":"4_CR3","DOI":"10.21203\/rs.3.rs-3227364\/v1"},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.ijcard.2019.01.046","volume":"288","author":"TA Daghistani","year":"2019","unstructured":"Daghistani, T.A., Elshawi, R., Sakr, S., Ahmed, A.M., Al-Thwayee, A., Al-Mallah, M.H.: Predictors of in-hospital length of stay among cardiac patients: a machine learning approach. Int. J. Cardiol. 288, 140\u2013147 (2019)","journal-title":"Int. J. Cardiol."},{"doi-asserted-by":"crossref","unstructured":"Gentimis, T., Alnaser, A.J., Durante, A., Cook, K., Steele, R.: Predicting hospital length of stay using neural networks on MIMIC III data. In: Proceedings of IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, pp. 1194\u20131201 (2017)","key":"4_CR5","DOI":"10.1109\/DASC-PICom-DataCom-CyberSciTec.2017.191"},{"key":"4_CR6","doi-asserted-by":"publisher","first-page":"e26","DOI":"10.1016\/j.ijmedinf.2010.10.001","volume":"80","author":"S Haas","year":"2011","unstructured":"Haas, S., Wohlgemuth, S., Echizen, I., Sonehara, N., Muller, G.: Aspects of privacy for electronic health records. Int. J. Med. Inform. 80, e26\u2013e31 (2011)","journal-title":"Int. J. Med. Inform."},{"doi-asserted-by":"crossref","unstructured":"Liu, P., et al.: Identify hospitalization cost drivers of traumatic fracture patients in China using quantile regression and backpropagation neural network (2023)","key":"4_CR7","DOI":"10.21203\/rs.3.rs-2962150\/v1"},{"key":"4_CR8","doi-asserted-by":"publisher","first-page":"109","DOI":"10.4258\/hir.2018.24.2.109","volume":"24","author":"H Maharlou","year":"2018","unstructured":"Maharlou, H., Kalhori, S.R.N., Shahbazi, S., Ravangard, R.: Predicting length of stay in intensive care units after cardiac surgery: comparison of artificial neural net-works and adaptive neuro-fuzzy system. Healthc. Inform. Res. 24, 109\u2013117 (2018)","journal-title":"Healthc. Inform. Res."},{"key":"4_CR9","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1007\/978-3-030-45688-7_21","volume-title":"Trends and Innovations in Information Systems and Technologies","author":"RN Mekhaldi","year":"2020","unstructured":"Mekhaldi, R.N., Caulier, P., Chaabane, S., Chraibi, A., Piechowiak, S.: Using machine learning models to predict the length of stay in a hospital setting. In: Rocha, \u00c1., Adeli, H., Reis, L.P., Costanzo, S., Orovic, I., Moreira, F. (eds.) WorldCIST 2020. AISC, vol. 1159, pp. 202\u2013211. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-45688-7_21"},{"unstructured":"Pedregosa, F., et al.: Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","key":"4_CR10"},{"key":"4_CR11","doi-asserted-by":"publisher","first-page":"1883","DOI":"10.4249\/scholarpedia.1883","volume":"4","author":"L Peterson","year":"2009","unstructured":"Peterson, L.: K-nearest neighbor. Scholarpedia 4, 1883 (2009)","journal-title":"Scholarpedia"},{"unstructured":"Quinlan, J.R.: C4.5: Programs for Machine Learning. Elsevier, Amsterdam (2014)","key":"4_CR12"},{"issue":"10","key":"4_CR13","first-page":"7874","volume":"34","author":"MM Rahman","year":"2022","unstructured":"Rahman, M.M., Kundu, D., Suha, S.A., Siddiqi, U.R., Dey, S.K.: Hospital patients\u2019 length of stay prediction: a federated learning approach. J. King Saud Univ.-Comput. Inf. Sci. 34(10), 7874\u20137884 (2022)","journal-title":"J. King Saud Univ.-Comput. Inf. Sci."},{"key":"4_CR14","doi-asserted-by":"publisher","DOI":"10.1002\/9780471722199","volume-title":"Linear Regression Analysis","author":"GAF Seber","year":"2003","unstructured":"Seber, G.A.F., Lee, A.J., Lee, R.A.: Linear Regression Analysis, 2nd edn. Wiley, New York (2003)","edition":"2"},{"key":"4_CR15","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1136\/jamia.1995.95202549","volume":"2","author":"S Shea","year":"1995","unstructured":"Shea, S., Sideli, R.V., Dumouchel, W., Pulver, G., Arons, R.R., Clay-ton, P.D.: Computer-generated informational messages directed to physicians: effect on length of hospital stay. J. Am. Med. Inform. Assoc. 2, 58\u201364 (1995)","journal-title":"J. Am. Med. Inform. Assoc."},{"unstructured":"http:\/\/www.health.ny.gov\/statistics\/sparcs\/datadic.htm","key":"4_CR16"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Proceedings of the 10th International Conference on Advanced Intelligent Systems and Informatics 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-77299-3_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T14:07:01Z","timestamp":1735654021000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-77299-3_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031772986","9783031772993"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-77299-3_4","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"type":"print","value":"2367-4512"},{"type":"electronic","value":"2367-4520"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"1 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AISI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Intelligent Systems and Informatics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cairo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Egypt","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aisi2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/egyptscience.net\/AISI24\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}