Foundation models for generalist medical artificial intelligence

The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine. We expect that GMAI-enabled applications will challenge current strategies for regulating and validating AI devices for medicine and will shift practices associated with the collection of large medical datasets.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 We propose a new paradigm for medical AI, which we refer to as generalist medical AI (GMAI).
• 2 GMAI models will be capable of carrying out a diverse set of tasks using very little or no task-specific labelled data.
• 3 Built through self-supervision on large, diverse datasets, GMAI will flexibly interpret different combinations of medical modalities, including data from imaging, electronic health records, laboratory results, genomics, graphs or medical text.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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