Clinical trial · Observational
AI-Driven Cancer Diagnosis and Prediction With EHR
AI-Based Cancer Diagnosis and Prediction Using Electronic Health Records
NCT06791473CI-TRIAL-00092803recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This is a multi-center, clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for identifying and diagnosing cancer, leveraging multimodal health data.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Tumor | Neoplasm | ALIAS | 0.90 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| AI-Based Diagnostic and Prognostic Model | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- label
- Healthy Cohort
- description
- This group consists of individuals without any diagnosed cancer. Participants in this cohort will serve as the control group for comparison to the experimental group. No interventions or treatments will be administered to this cohort, as they represent a baseline of healthy individuals.
- interventionNames
- Diagnostic Test: AI-Based Diagnostic and Prognostic Model
- label
- Tumor Cohort
- description
- This group consists of individuals diagnosed with cancer, including various types. Participants in this cohort will serve as the experimental group for evaluating the effectiveness of the early prediction model in identifying cancer risks and improving diagnostic accuracy.
- interventionNames
- Diagnostic Test: AI-Based Diagnostic and Prognostic Model
Primary outcomes (2)
- measure
- Area Under the Curve (AUC)
- timeFrame
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 0 Years
- Maximum age
- 90 Years
Show eligibility criteria text
Inclusion Criteria: 1、Patients with comprehensive electronic health records (EHRs), including medical history, laboratory test results, imaging data, and genetic data (if available). 2\. Individuals without severe cognitive impairments or conditions that would prevent them from providing informed consent or participating in the study. 3\. Parents or guardians must provide informed consent for minors, while adult participants must provide informed consent for themselves. Exclusion Criteria: 1. Patients with incomplete or missing key electronic health record data or insufficient follow-up data. 2. Individuals with severe cognitive disorders or other terminal illnesses that would prevent meaningful participation. 3. Pregnant women (although pediatric cancers are being considered, pregnant women would be excluded for safety reasons).
References
Publications (0)
Data not yet available
No reference posted for this study.