Two AI models demonstrate their potential for patient management using simulations and real-world data
Nature has published two independent studies demonstrating the ability of large language models based on artificial intelligence (AI) to support different stages of patient management in controlled settings. The first study analysed MIRA, an AI agent that operates within electronic health records, which achieved a diagnostic accuracy of nearly 88%, compared with 78% for a panel of physicians. The second study evaluated AMIE, a conversational clinical reasoning model, against 21 primary care physicians across 100 multi-visit scenarios. AMIE achieved performance comparable to, and in some cases better than, that of physicians in terms of treatment accuracy, test ordering, and adherence to clinical guidelines. The models are based on simulations or retrospective data, which limits the strength of the conclusions that can be drawn. The findings are consistent with another model published in Science last April.