JAMA+ AI Conversations AI, Health Care, and What to Expect in 2026
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Oct 9, 2025 Explore how AI is transforming health care by 2026, from detecting hidden brain lesions to enhancing medical imaging. Discover the debate on AI's role in radiology and its potential to reduce clinician burnout. Dive into innovative studies showcasing AI translation capabilities and confronting public perceptions of AI in medicine. Learn about the push for rigorous trials to validate AI health tools and the rise of direct-to-consumer AI products, highlighting both opportunities and risks for the future.
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Graph Neural Nets Reveal Hidden Lesions
- Graph neural networks can detect subtle brain lesions missed by radiologists, improving diagnosis of focal cortical dysplasia.
- Yulin Hswen highlights that mapping brain surface connections helps spot hidden abnormalities beyond pixel-level image analysis.
Don't Forget Predictive Models
- Traditional predictive models remain valuable for deterministic clinical risk scoring and benchmarking.
- Roy H. Perlis argues we need independent, real-world comparisons and prospective trials for early warning scores.
LLMs Can Translate Clinical Instructions
- Large language models can produce clinically accurate translations that match or exceed professional translators.
- Yulin Hswen notes ChatGPT-4 translated pediatric instructions into Spanish with fewer errors and reviewer preference.