Artificial Intelligence (AI) in Diagnosis
18
8
8
3
Key Insights
Highlights
Success Rate
100% trial completion (above average)
Clinical Risk Assessment
Based on trial outcomes
Moderate Risk
Score: 50/100
0.0%
0 terminated out of 18 trials
100.0%
+13.4% vs benchmark
0%
0 trials in Phase 3/4
0%
0 of 3 completed with results
Key Signals
Data Visualizations
Phase Distribution
Trial Status
Trial Success Rate
Benchmark: 86.6%
Based on 3 completed trials
Clinical Trials (18)
Development and Prospective Validation of an AI-Based Diagnostic Model for Hepato-Pancreato-Biliary Diseases
AI-Based Prediction of Stage and Survival in Non-Small Cell Lung Cancer: A Retrospective Study
Does AI Make Clinicians More Appropriately Confident? A Randomized Study in Preterm Birth Prediction
Diagnostic Accuracy of GPT-4o and Claude 4.6 Sonnet in Turkish ED Anamnesis Notes
Comparison of Digital Analysis and Artificial Intelligence for Cephalometric Tracing
Diagnostic Accuracy of GPT-4o and Claude for HEART Score Calculation in Chest Pain
AI-Assisted Chest-CT Reporting for Enhanced Speed and Quality (The DOUBLE-ACE Study)
The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice
AI-Based Diabetic Foot Recurrence Cohort
A Deep-Learning-Enabled Electrocardiogram for Detecting Pulmonary Hypertension
AI Telemedicine Support for Primary Care Physicians in El Salvador
Reasoning Enrichment With Feedback From IA in NEphrology Trial
Comparing Artificial Intelligence and Physicians: A Vignette-Based Study in Pediatric Clinical Decision-Making
A Multi-center Study on Artificial Intelligence-Based Quantitative Evaluation of Echocardiography
Human-AI Collaborative INSIGHT Diagnostic Workflow for in Breast Cancer With Extensive Intraductal Component
The Impact of Artificial Intelligence on Dentists' Decision-Making Process During Caries Detection
AI-Based Prediction of Lymph Node Metastasis in Gastric Cancer Using Preoperative Multimodal Data
Deep Learning-Based Analysis of Colorectal Cancer Pathology Images: An Innovative Approach for Predicting Colorectal Cancer Subtypes