Achieving inclusive healthcare through integrating education and research with AI and personalized curricula
Abstrak
Abstract Background Precision medicine promises significant health benefits but faces challenges such as 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) such as Generative Pretrained Transformer (GPT) and Claude highlights the importance of making complex data accessible to non-specialists. Methods We evaluated the Stanford Data Ocean (SDO) precision medicine training program’s learning outcomes, AI Tutor performance, and learner satisfaction by assessing self-rated competency on key learning objectives through pre- and post-learning surveys, along with formative and summative assessment completion rates. We also analyzed AI Tutor accuracy and learners’ self-reported satisfaction, and post-program academic and career impacts. Additionally, we demonstrated the capabilities of the AI Data Visualization tool. Results SDO demonstrates the ability to improve learning outcomes for learners from broad educational and socioeconomic backgrounds with the support of the AI Tutor. The AI Data Visualization tool enables learners to interpret multi-omics and wearable data and replicate research findings. Conclusions SDO strives to mitigate challenges in precision medicine through a scalable, cloud-based platform that supports data management for various data types, advanced research, and personalized learning. SDO provides AI Tutors and AI-powered data visualization tools to enhance educational and research outcomes and make data analysis accessible to users from broad 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.
Topik & Kata Kunci
Penulis (33)
Amir Bahmani
Kexin Cha
Arash Alavi
Amit Dixit
Antony Ross
Ryan Park
Francesca Goncalves
Shirley Ma
Paul Saxman
Ramesh Nair
Ramin Akhavan-Sarraf
Xin Zhou
Meng Wang
Kévin Contrepois
Jennifer Li-Pook-Than
Emma Monte
David Jose Florez Rodriguez
Jaslene Lai
Mohan Babu
Abtin Tondar
Sophia Miryam Schüssler-Fiorenza Rose
Ilya Akbari
Xinyue Zhang
Kritika Yegnashankaran
Joseph Yracheta
Kali Dale
Alison Derbenwick Miller
Scott Edmiston
Eva M. McGhee
Camille Nebeker
Joseph C. Wu
Anshul Kundaje
Michael Snyder
Akses Cepat
- Tahun Terbit
- 2025
- Sumber Database
- DOAJ
- DOI
- 10.1038/s43856-025-01034-y
- Akses
- Open Access ✓