170431 20260420103355.0 doi 10.3389/fmed.2026.1827042 sideral 148898 ART-2026-148898 eng Handa, Palak Editorial: Advancing gastrointestinal disease diagnosis with interpretable AI and edge computing for enhanced patient care 2026 Editorial on the Research Topic Advancing gastrointestinal disease diagnosis with interpretable AI and edge computing for enhanced patient care For decades, progress in gastrointestinal (GI) diagnostics has followed a familiar pattern: better optics, higher resolution imaging, and increasingly refined classification systems interpreted by trained clinicians (1). Despite remarkable advances in endoscopy and imaging technologies, clinical decision-making has remained fundamentally human-limited (2, 3). Detection depends on attention; interpretation depends on experience; and workflow efficiency depends on time. Modern gastroenterology rarely struggles to capture images; the challenge lies in the clinician's ability to review and interpret the sheer volume produced. Access copy available to the general public Unrestricted info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/other info:eu-repo/semantics/publishedVersion Goel, Nidhi Krishnan, Sri Gunjan, Deepak Koulaouzidis, Anastasios Lanas, Angel Universidad de Zaragoza (orcid)0000-0001-5932-2889 1007 610 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Medicina 13 (2026), 1827042 [4 p.] Front. med. Frontiers in Medicine 2296-858X 439329 http://zaguan.unizar.es/record/170431/files/texto_completo.pdf Versión publicada 2001867 http://zaguan.unizar.es/record/170431/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:170431 articulos driver 2026-04-18-10:49:26 ARTICLE