Development and Validation of an Interpretable Machine Learning Model for Staging Helicobacter pylori–Initiated Intestinal-Type Gastric Cancer in the Correa Cascade: Cross-Sectional Study
Background: Gastric cancer (GC) is one of the most common malignant tumors worldwide, with –associated intestinal-type gastric cancer (IGC) being the most prevalent subtype, accounting for approximately 85% of cases. Because most patients are diagnosed at intermediate or advanced stages, early screening and accurate stage stratification of IGC progression remain major clinical challenges. Objective: This study aimed to develop an interpretable machine learning (ML) model that leverages routine l
Record details
Published: 7 August 2026
Source: JMIR (Journal of Medical Internet Research)
Category: Research
Topics: Healthcare
Retrieved: 8 August 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Deep learning in precision phytopathology: a comprehensive survey of CNN architectures for disease detection and severity quantification
Artificial Intelligence Review · 8 August 2026
Strategies to improve treatment adherence of digital health applications—rapid review and mixed-method analysis
AI & Society · 8 August 2026
Machine Learning to Identify Point-of-Care Ultrasound and Evaluate Standardized Documentation: Retrospective Operational Cohort Study
JMIR (Journal of Medical Internet Research) · 7 August 2026
Heterogeneous Associations Between Frequent Virtual Communication and Loneliness Among Older Adults: Observational Analysis
JMIR (Journal of Medical Internet Research) · 7 August 2026
Clinician Participation in Innovation Labs at University Hospitals: Mixed Methods Study
JMIR (Journal of Medical Internet Research) · 7 August 2026
Conversational Large Language Models for Vestibular Diagnosis in Outpatient Clinics: Prospective Multicenter Diagnostic Accuracy Study
JMIR (Journal of Medical Internet Research) · 7 August 2026
How to cite this record
ethics.ai (7 August 2026), “Development and Validation of an Interpretable Machine Learning Model for Staging Helicobacter pylori–Initiated Intestinal-Type Gastric Cancer in the Correa Cascade: Cross-Sectional Study,” evidence record 17500, https://ethics.ai/record/17500 (originally published by JMIR (Journal of Medical Internet Research)).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.