{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T21:39:28Z","timestamp":1790890768541,"version":"4.1.0"},"reference-count":76,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T00:00:00Z","timestamp":1747008000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>Intradialytic hypotension (IDH) is a critical complication in patients with chronic kidney disease undergoing dialysis, affecting both patient safety and treatment efficacy. This study examines the application of advanced machine learning techniques, combined with metaheuristic optimization methods, to improve predictive models for intradialytic hypotension (IDH) in hemodialysis patients. Given the critical nature of IDH, which can lead to significant complications during dialysis, the development of effective predictive tools is vital for improving patient safety and outcomes. Dialysis session data from 758 patients collected between January 2016 and October 2019 were analyzed. Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. Among the evaluated models, the XGBoost classifier showed superior performance, achieving a macro F-score of 0.745 with a recall of 0.756 and a precision of 0.718. These results highlight the effectiveness of the combined approach for early identification of patients at risk for IDH, minimizing false negatives, and improving clinical decision-making in nephrology.<\/jats:p>","DOI":"10.3390\/biomimetics10050314","type":"journal-article","created":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T10:58:07Z","timestamp":1747047487000},"page":"314","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7723-7012","authenticated-orcid":false,"given":"Felipe","family":"Cisternas-Caneo","sequence":"first","affiliation":[{"name":"Escuela de Ingenier\u00eda Inform\u00e1tica, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Avenida Brasil 2241, Valpara\u00edso 2362807, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2323-192X","authenticated-orcid":false,"given":"Mar\u00eda","family":"Santamera-Lastras","sequence":"additional","affiliation":[{"name":"Department of Medicine and Medical Specialties, Universidad de Alcal\u00e1, Alcal\u00e1 de Henares, 28805 Madrid, Spain"},{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Alcal\u00e1 de Henares, 28805 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-9934-5250","authenticated-orcid":false,"given":"Jos\u00e9","family":"Barrera-Garcia","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda Inform\u00e1tica, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Avenida Brasil 2241, Valpara\u00edso 2362807, Chile"},{"name":"Escuela de Negocios y Econom\u00eda, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Amun\u00e1tegui 1838, Vi\u00f1a del Mar 2580129, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5500-0188","authenticated-orcid":false,"given":"Broderick","family":"Crawford","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda Inform\u00e1tica, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Avenida Brasil 2241, Valpara\u00edso 2362807, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5755-6929","authenticated-orcid":false,"given":"Ricardo","family":"Soto","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda Inform\u00e1tica, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Avenida Brasil 2241, Valpara\u00edso 2362807, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0359-7921","authenticated-orcid":false,"given":"Crist\u00f3bal","family":"Brante-Aguilera","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda en Construcci\u00f3n y Transporte, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Avenida Brasil 2147, Valpara\u00edso 2362804, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1365-9280","authenticated-orcid":false,"given":"Alberto","family":"Garc\u00e9s-Jim\u00e9nez","sequence":"additional","affiliation":[{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Alcal\u00e1 de Henares, 28805 Madrid, Spain"},{"name":"Department of Computer Science, Universidad de Alcal\u00e1, Alcal\u00e1 de Henares, 28805 Madrid, Spain"},{"name":"Ram\u00f3n y Cajal Institute for Health Research (IRYCIS), 28034 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9125-9311","authenticated-orcid":false,"given":"Diego","family":"Rodriguez-Puyol","sequence":"additional","affiliation":[{"name":"Department of Medicine and Medical Specialties, Universidad de Alcal\u00e1, Alcal\u00e1 de Henares, 28805 Madrid, Spain"},{"name":"Ram\u00f3n y Cajal Institute for Health Research (IRYCIS), 28034 Madrid, Spain"},{"name":"Nephrology Department and Research Foundation, Hospital Universitario Principe de Asturias, 28805 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6897-8262","authenticated-orcid":false,"given":"Jos\u00e9 Manuel","family":"G\u00f3mez-Pulido","sequence":"additional","affiliation":[{"name":"Health Computing and Intelligent Systems Research Group (HCIS), Universidad de Alcal\u00e1, Alcal\u00e1 de Henares, 28805 Madrid, Spain"},{"name":"Department of Computer Science, Universidad de 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