Other
deep learning
deep learning is an intervention with 5 clinical trials. Historical success rate of 100.0%.
Total Trials
5
Max Phase
—
Type
DIAGNOSTIC TEST
Molecule
—
Success Metrics
Clinical Success Rate
100.0%
Based on 1 completed trials
Completion Rate
100%(1/1)
Active Trials
0(0%)
Results Posted
0%(0 trials)
Phase Distribution
Ph not_applicable
1
20%
Phase Distribution
0
Early Stage
0
Mid Stage
0
Late Stage
Phase Distribution1 total trials
N/ANon-phased studies
1(100.0%)
Highest Phase Reached
UnknownTrial Status & Enrollment
Completion Rate
100.0%
1 of 1 finished
Non-Completion Rate
0.0%
0 ended early
Currently Active
0
trials recruiting
Total Trials
5
all time
Status Distribution
Completed(1)
Other(4)
Detailed Status
unknown4
Completed1
Development Timeline
Analytics
Development Status
Total Trials
5
Active
0
Success Rate
100.0%
Most Advanced
N/A
Trials by Phase
N/A1 (100.0%)
Trials by Status
unknown480%
completed120%
Recent Activity
0 active trials
Showing 5 of 5
unknownnot_applicable
E-CLAIR: Efficiency and Cost-effectiveness of Artificial Intelligence Based Diabetic Retinopathy Screening in Flanders
NCT05391659
unknown
A Study on Vertebral Bone Strength by Micro-CT-Like Image
NCT04954417
unknown
Deep-learning Based Classification of Spine CT
NCT03790930
completed
A Deep Learning Approach to Submerged Teeth Classification and Detection
NCT04309851
unknown
Automatic Diagnosis of Spinal Stenosis on CT
NCT03746561
Clinical Trials (5)
Showing 5 of 5 trials
NCT05391659Not Applicable
E-CLAIR: Efficiency and Cost-effectiveness of Artificial Intelligence Based Diabetic Retinopathy Screening in Flanders
NCT04954417
A Study on Vertebral Bone Strength by Micro-CT-Like Image
NCT03790930
Deep-learning Based Classification of Spine CT
NCT04309851
A Deep Learning Approach to Submerged Teeth Classification and Detection
NCT03746561
Automatic Diagnosis of Spinal Stenosis on CT
All 5 trials loaded
Drug Details
- Intervention Type
- DIAGNOSTIC TEST
- Total Trials
- 5