doi:10.3389/fmed.2026.1827042engHanda, PalakGoel, NidhiKrishnan, SriGunjan, DeepakKoulaouzidis, AnastasiosLanas, AngelEditorial: Advancing gastrointestinal disease diagnosis with interpretable AI and edge computing for enhanced patient careART-2026-148898Editorial 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.2026http://zaguan.unizar.es/record/17043110.3389/fmed.2026.1827042http://zaguan.unizar.es/record/170431oai:zaguan.unizar.es:170431Frontiers in Medicine 13 (2026), 1827042 [4 p.]byhttps://creativecommons.org/licenses/by/4.0/deed.esinfo:eu-repo/semantics/openAccess