Using AI to Diagnose Deep Vein Thrombosis with Ultrasound
Author Information
Author(s): Nothnagel Kerstin, Aslam Mohammed Farid
Primary Institution: University of Bristol
Hypothesis
Can AI-guided point-of-care ultrasound effectively diagnose deep vein thrombosis by non-specialists?
Conclusion
AI-guided ultrasound can help non-specialists diagnose deep vein thrombosis effectively, potentially reducing the need for formal scans.
Supporting Evidence
- 91% of scans had sufficient quality for diagnosis.
- Sensitivity was 100% and specificity was 90.57%.
- 53% of participants were classified as low risk, potentially avoiding formal scans.
Takeaway
This study shows that a smartphone app can help doctors without special training take pictures of veins to check for blood clots.
Methodology
Patients underwent AI-guided ultrasound scans followed by formal scans, with images reviewed remotely by specialists.
Potential Biases
Potential bias from the non-specialist operators and the retrospective nature of the study.
Limitations
The study had a small number of positive DVT cases and was retrospective, requiring further validation.
Participant Demographics
The participants were predominantly older females with an average age of 69.7 years.
Statistical Information
P-Value
0.0001
Confidence Interval
95% CI = 99.12% to 100%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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