A
recent narrative review concluded that artificial intelligence (AI) has a
significant impact on gastroenterology, with substantial evidence supporting
its diagnostic applications, particularly in colonoscopy and histological
grading.
The
review highlighted that AI presents solutions for adherence, personalization,
and support for patients with irritable bowel syndrome (IBS), gastroesophageal
reflux disorder (GERD), inflammatory bowel disease (IBD), functional dyspepsia (FD),
and related disorders, as diet plays a crucial role in symptom management of
these disorders.
The
authors suggested that AI-enhanced nutrition platforms and telehealth coaching
can improve adherence and achieve outcomes comparable to in-person management,
transforming gastrointestinal treatment into a personalised paradigm that
extends beyond hospitals.
This narrative review
was published in January 2026 in the Journal Cureus.
Applications
of AI in Gastroenterology
Artificial
intelligence (AI), which leverages machine learning (ML) and deep learning (DL)
to analyse large datasets, identify patterns, and enhance clinical
decision-making, is increasingly utilised in gastroenterology. Artificial
intelligence (AI) has demonstrated significant benefits in diagnosing
gastrointestinal (GI) diseases. The additional applications include
AI-assisted
colonoscopy improves the adenoma detection rate (ADR) and polyp detection rate
(PDR) compared with conventional methods. AI
reduces operator-dependent variability, allowing trainees to achieve ADR levels
comparable to those of expert endoscopists. AI
models assist with histological scoring in ulcerative colitis, reducing
subjectivity and expediting clinical trials through automated endpoint
assessments. AI
achieves gastroenterologist-level accuracy in detecting erosions, ulcers, and
bleeding during capsule endoscopy, reducing video review times and minimizing
missed anomalies. AI-driven
nutritional treatments use ML algorithms to analyze data and refine dietary
recommendations, unlike conventional platforms that use static guidance without
personalization.
AI-Driven
Approaches to Address Resource Constraints in Gastrointestinal Nutrition Care
Gastroenterologists
often lack sufficient time and resources during regular appointments to provide
extensive dietary counselling, and many facilities lack trained dietitians or
behavioural specialists. AI technologies present innovative solutions to these
challenges.
Natural
Language Processing (NLP) applications can offer personalised dietary advice,
decreasing dependence on online sources. Machine learning helps identify
patients at risk, allowing for proactive engagement by care providers.
AI-driven chatbots extend support beyond clinic visits by offering
cost-effective reminders and immediate assistance. They also support multiple
languages and incorporate socioeconomic health factors into their frameworks.
With careful deployment- focusing on bias reduction and data privacy- AI can
enhance access to lifestyle support and help minimise health inequities.
Future
Application of AI in Gastroenterology
Digital
Symptom Logging and AI-Augmented Diet Applications: Patient-centred mobile applications
with meal logging, symptom tracking, and cultural nutrition databases provide
opportunities for AI in gastroenterology by correlating dietary patterns with
disease progression.
Integration
With Wearables, Microbiome, and Predictive Analytics: The next step is to integrate
wearables, biomarkers, and microbiome profiling with AI-driven dietary systems.
Glucose monitors, pH sensors, and accelerometers track physiological signals
associated with dietary triggers. Machine learning can predict IBD hospitalisations,
and expanding these models with diet-symptom data may help predict flare-ups.
FDA-Cleared
Digital Therapeutics and Precision Nutrition Ecosystems: AI-driven platforms could be
approved as digital therapeutics for conditions such as functional GI
disorders, IBD, and gastroparesis. These tools may qualify for reimbursement in
routine practice, following precedents in behavioural medicine and diabetes
management. AI in daily life through smart nutrition systems can reduce costs
by preventing procedures and improving patient care.
Possible
Stakeholder Implications
Current
AI efforts in gastroenterology focus on diagnostics, including polyp detection,
histological grading, and image-based disease classification. Integrating AI
into dietary and lifestyle domains meets key needs by delivering personalised
care, feedback, and behavioural reinforcement between visits, capabilities
lacking in conventional care models. When developed ethically with data
protection in mind, AI can transform dietary management for GI disorders by
encouraging proactive treatment, increasing patient independence, and reducing
unnecessary physician consultations.
Reference: Ajmera K, Patel O, Shah N. Artificial
Intelligence in Gastroenterology: Beyond Diagnostics and Toward Lifestyle and
Dietary Interventions for Gastrointestinal Disorders. Cureus 18(1):
e100976. Published January 07, 2026. DOI
10.7759/cureus.100976