Diagnostic assist with rigorous clinical eval
Anonymised engagement: medical imaging assist model with strict evaluation protocol, explainability layer, and drift monitoring for a HealthTech R&D team.
Stack: PyTorch · OpenCV · ONNX · Evidently · FastAPI · Docker
Challenge
Clinical stakeholders required transparent baselines, hold-out eval on domain data, and monitoring for data drift after deployment.
Solution
TechieYan delivered a CNN-based assist pipeline with Grad-CAM explainability, documented sensitivity/specificity on client hold-out sets, and Evidently-powered drift dashboards.
Outcomes
- Documented eval harness with client-approved hold-out protocol
- Explainability overlays for clinician review workflows
- Production monitoring catching drift before accuracy degradation
- Edge-capable quantized model variant for low-bandwidth sites
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