Related Experiment Video
Updated: Sep 11, 2025
qPCR Is a Sensitive and Rapid Method for Detection of Cytomegaloviral DNA in Formalin-fixed, Paraffin-embedded Biopsy Tissue
Published on: July 9, 2014
Artificial intelligence-based multimodal model for the identification of ulcerative colitis with concomitant
Haozheng Liang1, Yuxuan Tian2, Gechong Ruan1
1Department of Gastroenterology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background:
Ulcerative colitis (UC), a chronic immune-mediated colon inflammation, impacts patients' quality of life. Immunosuppressive-treated UC patients are prone to opportunistic infections like cytomegalovirus (CMV) infection, which exacerbates UC, causes steroid resistance, and elevates surgery and mortality risks. Identifying CMV colitis from UC exacerbation is difficult due to overlapping symptoms and low biopsy detection rates.
Objectives:
To develop an artificial intelligence (AI)-based multimodal model for early identification of UC with concomitant CMV colitis.
Design:
This was a retrospective diagnostic study.
Methods:
A total of 174 moderate to severe UC patients (87 with CMV colitis) from 2015 to 2023 in Peking Union Medical College Hospital were enrolled retrospectively. A total of 3345 colonoscopy images were collected. The dataset was split into training (70%) and testing (30%) sets. A multimodal dynamic affine transformation (DAFT) model integrating clinical biomarkers and endoscopic images was constructed, along with ResNet and SeNet models. Model performance was evaluated using accuracy, sensitivity, specificity, positive and negative predictive values from the confusion matrix.
Results:
UC patients with CMV colitis had distinct clinical characteristics. The multimodal DAFT model outperformed ResNet and SeNet in distinguishing UC with CMV colitis, with higher accuracy (0.91), sensitivity (0.87), and specificity (0.93).
Conclusion:
AI application offers a promising way to enhance early identification of UC with CMV colitis. The multimodal model combining clinical and endoscopic data can assist clinicians in accurate and timely diagnosis.
Related Concept Videos
01:26Imaging Studies III: Gastrointestinal Motility Studies and Virtual Colonoscopy
Radionuclide Testing
Radionuclide testing is a sophisticated medical technique for assessing gastrointestinal motility. It focuses on gastric emptying and colonic transit time. Radioactive markers track the movement of food through the digestive system, providing insights into gastrointestinal disorders.
In gastric emptying studies, a meal's liquid and...
01:27Inflammatory Bowel Disease I: Ulcerative Colitis
Inflammatory bowel disease, or IBD, encompasses a group of disorders characterized by chronic inflammation or ulceration of the gastrointestinal tract.
Risk Factors
The exact cause of IBD remains unclear, although it is believed to be due to a mix of genetic, environmental, microbial, and immune factors. Genetic factors are significant in determining susceptibility to IBD, with family history being a critical risk factor. Individuals with a first-degree relative who has IBD are at...
01:28Peptic Ulcer Disease III: Clinical Manifestations and Diagnostic Studies
Few clinical manifestations differentiate gastric ulcers from duodenal ulcers. Distinctions in the location, timing, and pain relief are crucial for healthcare providers in differentiating between gastric and duodenal ulcers during clinical assessments.
01:30Irritable Bowel Syndrome II: Clinical Features and Diagnostic Evaluation
Irritable Bowel Syndrome (IBS) is classified into subtypes based on the predominant bowel habits as determined by the Bristol Stool Form Scale (BSFS). The subtypes are:
01:29Drugs for Treatment of Ulcerative Colitis in IBD