ArticleNPJ digital medicine2023
Improving bowel preparation for colonoscopy with a smartphone application driven by artificial intelligence.
Article in NPJ digital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Diagnostic performance of AI-assisted endoscopy diagnosis of digestive system tumors: an umbrella review.Frontiers in oncology · 2025Pooled it
- Use of an AI Image Recognition-Based Smartphone App in Personalized Bowel Preparation Before Colonoscopy: Prospective Randomized Controlled Trial.JMIR mHealth and uHealth · 2026Trial
- Design and evaluation of a colon cancer mobile application.BMC gastroenterology · 2024Trial
- Feasibility of a Stool State Check App Using AI During Bowel Preparation Before Colonoscopy: Multicenter Prospective Study (SCAN Study).JMIR mHealth and uHealth · 2026Observational
- Korean clinical practice guidelines for bowel preparation before colonoscopy.Clinical endoscopy · 2026Review
- AI-assisted assessment of bowel preparation from patient-generated images for pre-procedure triage.Scientific reports · 2026Article
- AI-Enhanced Vibrational Capsule for Minimally Invasive Detection of Abnormal Bowel Tissue.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Human-machine collaboration in colorectal cancer screening: a narrative review of artificial intelligence-assisted colonoscopy.Frontiers in medicine · 2026Review
- Artificial Intelligence in Gastrointestinal Endoscopy: Current Advances, Clinical Integration, and Future Directions: A Narrative Review.Clinical and experimental gastroenterology · 2026Review
- Fusion color space analysis of tongue image characteristics in different stages of metastatic colorectal cancer and three-class model construction.Frontiers in physiology · 2026Article
- Quality of Bowel Preparation in the General Population.Medicina (Kaunas, Lithuania) · 2025Article
- Research progress on intestinal preparation before colonoscopy.World journal of gastrointestinal endoscopy · 2025Review
- Artificial intelligence in colonoscopy: Enhancing quality indicators for optimal patient outcomes.World journal of gastroenterology · 2025Review
- Clinical outcomes of bowel preparation education strategies in colonoscopy: An evidence map of systematic reviews.Medicine · 2025Article
- Clinical significance of computer-aided quality assessment systems in colonoscopy: a comprehensive review.Clinical endoscopy · 2025Review
- A Prospective Randomized Study to Predict Bowel Preparation Quality Prior to Colonoscopy: Comparison of Two Stool Collection Methods for the Objective Assessment of Final Rectal Effluent Clarity.Diagnostics (Basel, Switzerland) · 2025Article
- Derivation and validation of a prediction model for inadequate bowel preparation in Chinese outpatients.Scientific reports · 2025Observational
- Article
- Text Message System for the Prediction of Colonoscopy Bowel Preparation Adequacy Before Colonoscopy: An Artificial Intelligence Image Classification Algorithm Based on Images of Stool Output.Gastro hep advances · 2025Article
- Effectiveness of a Mobile Health Application for Educating Outpatients about Bowel Preparation.Healthcare (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
21 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Optimal bowel preparation is a prerequisite for a successful colonoscopy; however, the rate of inadequate bowel preparation remains relatively high. In this study, we establish a smartphone app that assesses patient bowel preparation using an artificial intelligence (AI)-based prediction system trained on labeled photographs of feces in the toilet and evaluate its impact on bowel preparation quality in colonoscopy outpatients. We conduct a prospective, single-masked, multicenter randomized clinical trial, enrolling outpatients who own a smartphone and are scheduled for a colonoscopy. We screen 578 eligible patients and randomize 524 in a 1:1 ratio to the control or AI-driven app group for bowel preparation. The study endpoints are the percentage of patients with adequate bowel preparation and the total BBPS score, compliance with dietary restrictions and purgative instructions, polyp detection rate, and adenoma detection rate (secondary). The prediction system has an accuracy of 95.15%, a specificity of 97.25%, and an area under the curve of 0.98 in the test dataset. In the full analysis set (n = 500), adequate preparation is significantly higher in the AI-driven app group (88.54 vs. 65.59%; P < 0.001). The mean BBPS score is 6.74 ± 1.25 in the AI-driven app group and 5.97 ± 1.81 in the control group (P < 0.001). The rates of compliance with dietary restrictions (93.68 vs. 83.81%, P = 0.001) and purgative instructions (96.05 vs. 84.62%, P < 0.001) are significantly higher in the AI-driven app group, as is the rate of additional purgative intake (26.88 vs. 17.41%, P = 0.011). Thus, our AI-driven smartphone app significantly improves the quality of bowel preparation and patient compliance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.