Artificial intelligence in gastroenterology practice: Current perspectives and emerging prospects

Table 8 Summary of major artificial intelligence applications in gastroenterology by clinical setting, evidence level, and implementation readiness

Application	Clinical setting	Intended user	Evidence level	External validation	Regulatory status	Unresolved limitations
Colorectal polyp/adenoma detection (CADe)[61-65]	Screening/surveillance colonoscopy	Endoscopist	RCT meta-analysis	Yes	Approved in the United States, Europe, and Japan	No CRC-incidence/mortality data yet, slight increase in withdrawal time and non-neoplastic resections
Gastric neoplasia detection/characterization (CADe/CADx)[34,36-44]	Screening/surveillance endoscopy	Endoscopist	Prospective single/multicenter, including 2 single-center RCTs	Yes	Approved in Japan	Single-center RCTs, generalizability unclear
Colorectal polyp optical diagnosis (CADx, resect-and-discard)[66,67]	Screening colonoscopy	Endoscopist	Meta-analysis	Yes	Approved in Japan	Modest incremental benefit over unassisted diagnosis
IBD endoscopic/histologic activity assessment (PICaSSO/PHRI)[71-75]	IBD surveillance colonoscopy and pathology	Endoscopist, pathologist	Multicenter prospective	Yes	AI-assisted assessment of inflammatory activity in UC during colonoscopy approved in Europe and Japan	Not yet linked to hard outcomes (relapse, colectomy)
Esophageal cancer detection, staging and prognosis[20-24]	Screening and surveillance endoscopy	Endoscopist, including non-experts	Prospective multicenter, international multicenter CADe study	Yes	Approved in Japan	Lesion-margin delineation remains difficult, survival models validated only in geographically restricted cohorts
CE lesion detection[46-53,55]	Small bowel diagnostic work-up	Gastroenterologist	Mixed retrospective/prospective, meta-analysis	Yes	Approved in United States	Reading-time benefit not yet linked to patient outcomes
Barrett’s esophagus detection[21,23]	Screening and surveillance endoscopy	Endoscopist	Retrospective/model development and validation study	Yes	Approved in Europe	Limited explainability
Liver fibrosis staging, lesion characterization and hepatitis-subtype classification[107-113,116-119]	Hepatology outpatient/radiology	Hepatologist, radiologist	Retrospective, some multicenter	Yes	Not approved	Performance decline on external validation, some reclassifications lack an absolute ground truth
Pancreatic cancer detection (radiomics, EHR-based risk models)[82-85]	Radiology/population risk stratification	Radiologist	Multi-institutional retrospective plus prospective validation	Yes	Not approved	No survival/patient-outcome data yet, low pretest prevalence limits real-world PPV
Biliary/ERCP-related AI (stone prediction, stricture characterization, PEP prediction)[95-102,104]	ERCP/cholangioscopy	Endoscopist	Retrospective single/multicenter	Yes	Not approved	Low PPV for PEP prediction, models built largely on trial-derived data

AI: Artificial intelligence; CADe: Computer-aided detection; CADx: Computer-aided diagnosis; CE: Capsule endoscopy; CRC: Colorectal cancer; HER: Electronic health record; ERCP: Endoscopic retrograde cholangiopancreatography; IBD: Inflammatory bowel disease; PEP: Post-endoscopic retrograde cholangiopancreatography pancreatitis; PHRI: PICaSSO Histologic Remission Index; PICaSSO: Paddington International Virtual ChromoendoScopy Score; PPV: Positive predictive value; RCT: Randomized controlled trial; UC: Ulcerative colitis.