The application of Large Language Models (LLMs) to create conversational agents (CAs) that can aid health professionals in their daily practice is increasingly popular, mainly due to their ability to understand and communicate in natural language.
Extracts clinical data from unstructured medical notes, validated on real and synthetic EHRs with over 90% semantic accuracy.
External validation of a machine learning model for early detection of chronic kidney disease in type 2 diabetes patients across low- and middle-income countries, demonstrating high sensitivity (90.05%) and potential utility in resource-limited primary care settings.
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