{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T07:29:48Z","timestamp":1774510188993,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:00:00Z","timestamp":1774310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Montana State University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Informatics"],"abstract":"<jats:p>Acute lymphoblastic leukemia (ALL) presents significant clinical challenges due to its genetic complexity and high relapse rates. While outcomes like length of stay (LOS), mortality, and total charges (TCs) are critical quality indicators, most existing models rely on static data and separate outcome modeling. This study utilized the HCUP National Inpatient Sample (NIS) to develop a dynamic, concurrent prediction model for prolonged LOS and mortality (PLOSM), alongside a framework for TCs. By integrating temporally updated patient information, the concurrent approach outperformed single-outcome models. Within the first seven days of hospitalization, the model achieved accuracy and precision above 90%, with recall and F1-scores exceeding 80%. Key predictors of these outcomes included age, race, insurance type, financial indicators, and elective surgery status. Notably, both prolonged LOS and mortality were significant drivers of TCs. By bridging predictive modeling and real-time clinical data, this framework enables data-driven decision-making to optimize patient management, enhance safety, and mitigate the financial burden of ALL care.<\/jats:p>","DOI":"10.3390\/informatics13040047","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T12:58:59Z","timestamp":1774357139000},"page":"47","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Concurrent Prediction of Length of Stay, Mortality, and Total Charges in Patients with Acute Lymphoblastic Leukemia Using Continuous Machine Learning"],"prefix":"10.3390","volume":"13","author":[{"given":"Jiahui","family":"Ma","sequence":"first","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, Norm Asbjornson College of Engineering, Montana State University, Norm Asbjornson Hall, Bozeman, MT 59717, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6628-4083","authenticated-orcid":false,"given":"Elizabeth","family":"Johnson","sequence":"additional","affiliation":[{"name":"Mark & Robyn Jones College of Nursing, Montana State University, Sherrick Hall 212, Bozeman, MT 59717, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8884-9743","authenticated-orcid":false,"given":"Bradley M.","family":"Whitaker","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Norm Asbjornson College of Engineering, Montana State University, Norm Asbjornson Hall, Bozeman, MT 59717, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2965-2470","authenticated-orcid":false,"given":"Faraz","family":"Dadgostari","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, Norm Asbjornson College of Engineering, Montana State University, Norm Asbjornson Hall, Bozeman, MT 59717, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hansjorg","family":"Schwertz","sequence":"additional","affiliation":[{"name":"Department of Occupational Medicine, Billings Clinic Bozeman, Bozeman, MT 59717, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2735-6464","authenticated-orcid":false,"given":"Bernadette","family":"McCrory","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Industrial Engineering, Norm Asbjornson College of Engineering, Montana State University, Norm Asbjornson Hall, Bozeman, MT 59717, USA"},{"name":"BioReD Hub, Montana State University, Bozeman, MT 59717, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"78","DOI":"10.12968\/bjon.2012.21.2.76","article-title":"Acute leukaemia: Making sense of a complex blood cancer","volume":"21","author":"Meenaghan","year":"2012","journal-title":"Br. 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