Achieving Inclusive Healthcare through Integrating Education and Research with AI and Personalized Curricula
Precision medicine promises significant health benefits but faces challenges such as the need for complex data management and analytics, interdisciplinary collaboration, and education of researchers, healthcare professionals, and participants. Addressing these needs requires the integration of compu...
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Published in | medRxiv : the preprint server for health sciences |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.08.2024
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Online Access | Get more information |
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Summary: | Precision medicine promises significant health benefits but faces challenges such as the need for complex data management and analytics, interdisciplinary collaboration, and education of researchers, healthcare professionals, and participants. Addressing these needs requires the integration of computational experts, engineers, designers, and healthcare professionals to develop user-friendly systems and shared terminologies. The widespread adoption of large language models (LLMs) like GPT-4 and Claude 3 highlights the importance of making complex data accessible to non-specialists. The Stanford Data Ocean (SDO) strives to mitigate these challenges through a scalable, cloud-based platform that supports data management for various data types, advanced research, and personalized learning in precision medicine. SDO provides AI tutors and AI-powered data visualization tools to enhance educational and research outcomes and make data analysis accessible for users from diverse educational backgrounds. By extending engagement and cutting-edge research capabilities globally, SDO particularly benefits economically disadvantaged and historically marginalized communities, fostering interdisciplinary biomedical research and bridging the gap between education and practical application in the biomedical field. |
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