{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T21:30:13Z","timestamp":1790285413891,"version":"4.1.0"},"reference-count":230,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Artificial Intelligence (AI) is transforming the healthcare field, offering innovative tools for improving the prediction, detection, and management of diseases. In nephrology, AI holds the potential to improve the diagnosis and treatment of kidney diseases, as well as the optimization of renal replacement therapies. In this review, a comprehensive analysis of recent literature works on artificial intelligence applied to nephrology is presented. Two key research areas structure this review. The first section examines AI models used to support early prediction of acute and chronic kidney disease. The second section explores artificial intelligence applications for hemodialytic therapies in renal insufficiency. Most studies reported high accuracy (e.g., accuracy \u2265 90%) in early prediction of kidney diseases, while fewer addressed therapy optimization and complication prevention, typically reporting moderate-to-high performance (e.g., accuracy \u2243 85%). Filling this gap and developing more accessible AI solutions that address all stages of kidney disease would therefore be crucial to support physicians\u2019 decision-making and improve patient care.<\/jats:p>","DOI":"10.3390\/bioengineering12101069","type":"journal-article","created":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T07:58:13Z","timestamp":1759305493000},"page":"1069","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Artificial Intelligence in Nephrology: From Early Detection to Clinical Management of Kidney Diseases"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6786-1764","authenticated-orcid":false,"given":"Alessia","family":"Nicosia","sequence":"first","affiliation":[{"name":"Department of Engineering, Universit\u00e0 degli Studi di Palermo, Viale delle Scienze Ed. 6, 90128 Palermo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3065-3291","authenticated-orcid":false,"given":"Nunzio","family":"Cancilla","sequence":"additional","affiliation":[{"name":"Department of Engineering, Universit\u00e0 degli Studi di Palermo, Viale delle Scienze Ed. 6, 90128 Palermo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9378-0285","authenticated-orcid":false,"given":"Jos\u00e9 David","family":"Mart\u00edn Guerrero","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Escola T\u00e8cnica Superior d\u2019Enginyeria, Universitat de Val\u00e8ncia (ETSE-UV), Despatx 3.2.26 Avgda. Universitat, s\/n., 46100 Val\u00e8ncia, Spain"},{"name":"Valencian Graduate School and Research Network of Artificial Intelligence (ValgrAI), 46010 Val\u00e8ncia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1305-0248","authenticated-orcid":false,"given":"Ilenia","family":"Tinnirello","sequence":"additional","affiliation":[{"name":"Department of Engineering, Universit\u00e0 degli Studi di Palermo, Viale delle Scienze Ed. 6, 90128 Palermo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0570-195X","authenticated-orcid":false,"given":"Andrea","family":"Cipollina","sequence":"additional","affiliation":[{"name":"Department of Engineering, Universit\u00e0 degli Studi di Palermo, Viale delle Scienze Ed. 6, 90128 Palermo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1111\/bju.14852","article-title":"Current Status of Artificial Intelligence Applications in Urology and Their Potential to Influence Clinical Practice","volume":"124","author":"Chen","year":"2019","journal-title":"BJU Int."},{"key":"ref_2","unstructured":"Russell, S.J., and Norvig, P. 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