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Welcome! In this issue, we spotlight our collaboration with Stanford Health Care evaluating the implementation of a generative AI tool to alleviate in-basket burden. We are also celebrating our contributions to a National Academy of Medicine report outlining a proposed universal AI code of conduct. These works and others are important milestones towards a future where healthcare is more accessible, responsive, and equitable. Continue reading to learn more and join us!
Steven Lin, MD, HEA3RT Director
Margaret Smith, MBA, HEA3RT Executive Director
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READ, DISCOVER, LISTEN, WATCH |
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Reducing EHR Burden with GPT-4
READ: Check out our recent collaboration results » outlining how AI-generated draft responses to patient messages could be a beacon of relief for providers, reducing burnout and administrative burden. [Twitter] |
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A Universal AI Code of Conduct
DISCOVER: AI in healthcare holds remarkable potential but there remains a need for unified standards for ethical application. Check out the recent National Academy of Medicine (NAM) report » proposing a universal AI code of conduct. |
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The Future of AI Chat
LISTEN: AI foundation models are the powerhouse behind today's groundbreaking advancements. Uncover how they're built, how to evaluate them, and the critical concerns that remain in this Podcast » from Stanford University. |
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Health Equity in AI Development
WATCH: Discover how HEA3RT and Google are shaping the path to more equitable healthcare through the development of diversified skin condition data for AI development. Watch this video » to learn more and explore the open-access dataset ». |
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Enabling Care Teams and Improving Patient Outcomes with AI
In an exciting article, HEA3RT’s collaboration on the implementation of EPIC's clinical deterioration index (CDI) at Stanford Health Care marks the first study demonstrating improved patient outcomes using the CDI tool. Click here » to explore how these findings are setting new standards in patient care, ensuring safer hospital environments.
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Amplifying Underserved Community Voices in AI Research
Check out this brief video » to discover how HEA3RT's collaboration with Google and the Blanca Alvarado Community Resource Center is bridging the gap between community, academia, and industry in healthcare AI research, and don't miss out on exploring the full Skin Day Report ».
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Preparing for the Future of AI in Healthcare
Explore the future of AI in healthcare through Dr. Shreya Shah's keynote at the 2024 Society of General Internal Medicine Regional Conference ». Delve into the potential of AI in augmenting patient care and optimizing physician workflows as Dr. Shah highlights current applications and examples from our work at HEA3RT. Click here » to see the full presentation.
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AMIA 2024 Clinical Informatics Conference
Unveiling a Large Language Model for Patient Message Classification to Automate Workflows and Reduce Inbox Burden
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STFM Annual Spring Conference
AI-Enabled Advance Care Planning on Inpatient Oncology: Feasibility, Acceptability, and Impact on Workflow
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XGM Annual Conference
Early Use of Augmented Response Technology (ART): AI-Generated Draft Replies for Patient InBasket Messages
View presentation »
Adoption and Early Use of Generative AI for Clinical Documentation with DAX Copilot
View presentation »
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SGIM California & Hawaii Regional Meeting
Leveraging Multimodal Artificial Intelligence to Overcome Barriers to Depression and Anxiety Screening
View poster »
Racial Disparities in Advance Care Planning: a pre-intervention study of an AI-based risk scoring tool
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North American Primary Care Research Group (NAPCRG) 51st Annual Meeting
Advancing Artificial Intelligence and Machine Learning for the Future of Primary Care and Population Health
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Thank you for taking the time to read our newsletter!
Visit our website if you would like to learn more about our work.
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About HEA3RT
HEA3RT is a translational research team in the Primary Care and Population Health Division at Stanford University. Our work covers a broad range of aims centered on the development and integration of artificial intelligence (AI) technologies that solve important, practical problems for patients, providers and health systems. We work with clinical, operational, and technical teams to advance the development of clinically relevant models, leveraging quality improvement, implementation science, design thinking, and traditional research methods.
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