# AI in Healthcare

AI is transforming diagnosis, clinical workflows, and medical research. This sub-article is an application-domain article under [Recent Topics](../recent.md).

## Diagnostics and Imaging
- Models read X-rays, pathology slides, and scans with high accuracy.
- Clinical validation and error rates remain critical.

## Clinical Documentation and Triage
- Ambient scribes draft notes and summaries.
- Triage and symptom checkers guide patients; safety requires human oversight.

## Drug Discovery and Genomics
- AI accelerates protein modeling (AlphaFold), drug design, and genomic analysis. See [Science Frontiers](scientific-frontiers.md).

## Medical Ethics and Regulation
- Accountability for AI errors is unresolved.
- Regulators (FDA, EMA) are defining approval pathways.
- Bias in datasets can harm underserved groups.

## Why It Matters
Healthcare is high-stakes; AI must be validated, explainable, and supervised before broad use.

## Sources
- FDA. *AI/ML-based medical devices guidance.*
- Jumper, J. et al. (2021). *AlphaFold.*

*Back to [Recent Topics](../recent.md).*