Hiding in plain sight – What does AI’s ability to detect patterns not visible to radiologists mean?
Emory University School of Medicine
Recent papers have demonstrated superhuman ability of AI models to predict demographics (including self-reported race, age and sex), biologic age, ICD codes, and healthcare costs from X-ray images. While the model performance in these cases is surprisingly good for tasks that are difficult for radiologists, challenges of model explainability makes it difficult to harness this ability for patient care. In this talk we will review
- Examples of cases where AI can detect “hidden signals” in X-ray images,
- Generalizability of these models to new data to determine their utility,
- Lay our a research roadmap to harness the ability of these models for patient care.