ArticleJournal of clinical medicine2020
Development of Machine Learning Model to Predict the 5-Year Risk of Starting Biologic Agents in Patients with Inflammatory Bowel Disease (IBD): K-CDM Network Study.
Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 4 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Pharmacoepidemiologic Research Based on Common Data Models: Systematic Review and Bibliometric Analysis.JMIR medical informatics · 2025Pooled it
- Prediction models for breast cancer-related lymphedema: a systematic review and critical appraisal.Systematic reviews · 2022Pooled it
- A Systematic Review of Artificial Intelligence and Machine Learning Applications to Inflammatory Bowel Disease, with Practical Guidelines for Interpretation.Inflammatory bowel diseases · 2022Pooled it
- Prediction Models for Prognosis of Cervical Cancer: Systematic Review and Critical Appraisal.Frontiers in public health · 2021Pooled it
- Preventing relapse in ulcerative colitis remission maintenance: machine learning prediction and reinforcement-learning herbal prescription optimization with external validation.Frontiers in medicine · 2026Article
- Early Risk Prediction for Biologic Therapy in Psoriasis Using Machine Learning Models Based on Routine Health Records.Journal of clinical medicine · 2025Article
- IgG4 unveiled: navigating the interplay with Crohn's disease - from immunology insights to machine learning.Annals of medicine and surgery (2012) · 2025Review
- Evolution of inflammatory bowel disease in Korea: a 60-year perspective on clinical and research development.Intestinal research · 2025Review
- Optimizing Lymphedema Management After Breast Cancer: Predictive Risk Models in Clinical Practice.Journal of surgical oncology · 2025Article
- Artificial intelligence to revolutionize IBD clinical trials: a comprehensive review.Therapeutic advances in gastroenterology · 2025Review
- Inter hospital external validation of interpretable machine learning based triage score for the emergency department using common data model.Scientific reports · 2024Article
- Performance of Machine Learning Algorithms for Predicting Disease Activity in Inflammatory Bowel Disease.Inflammation · 2023Article
- Article
- Machine Learning Can Predict the Probability of Biologic Therapy in Patients with Inflammatory Bowel Disease.Journal of clinical medicine · 2022Article
- Protected Health Information Recognition by Fine-Tuning a Pre-training Transformer Model.Healthcare informatics research · 2022Article
- Machine Learning Prediction Model for Inflammatory Bowel Disease Based on Laboratory Markers. Working Model in a Discovery Cohort Study.Journal of clinical medicine · 2021Article
- Artificial Intelligence in Gastroenterology-Walking into the Room of Little Miracles.Journal of clinical medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundThe incidence and global burden of inflammatory bowel disease (IBD) have steadily increased in the past few decades. Improved methods to stratify risk and predict disease-related outcomes are required for IBD.
aimThe aim of this study was to develop and validate a machine learning (ML) model to predict the 5-year risk of starting biologic agents in IBD patients.
methodWe applied an ML method to the database of the Korean common data model (K-CDM) network, a data sharing consortium of tertiary centers in Korea, to develop a model to predict the 5-year risk of starting biologic agents in IBD patients. The records analyzed were those of patients diagnosed with IBD between January 2006 and June 2017 at Gil Medical Center (GMC;
resultThe ML model for prediction of IBD-related outcomes at 5 years after diagnosis yielded an area under the curve (AUC) of 0.86 (95% CI: 0.82-0.92), in an internal validation study carried out at GMC. The model performed consistently across a range of other datasets, including that of the K-CDM network (AUC = 0.81; 95% CI: 0.80-0.85), in an external validation study.
conclusionThe ML-based prediction model can be used to identify IBD-related outcomes in patients at risk, enabling physicians to perform close follow-up based on the patient's risk level, estimated through the ML algorithm.
Indexed as
Identifiers
What OpenQuestion holds
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.