The Sustainably Advancing Health AI (SAHAI) Framework скачать в хорошем качестве

The Sustainably Advancing Health AI (SAHAI) Framework

As health systems rapidly adopt AI, they face a pivotal moment to align innovation with sustainability. The Sustainably Advancing Health AI (SAHAI) framework offers a roadmap for measuring and mitigating the energy, emissions, and cost impacts of AI implementation across applications, models, and data centers, while maintaining clinical performance and equity goals. This session highlights pathways for health leaders, policymakers, and national initiatives such as the Health AI Partnership (HAIP) to collaboratively advance responsible, climate-efficient, and economically sustainable AI in healthcare. -- Anu Ramachandran, MD, MPH Dr. Ramachandran is a Clinical Assistant Professor of Emergency Medicine at the University of California, San Francisco, and previously a Postdoctoral Fellow in Medical Informatics at Stanford University. Her research explores how informatics and technology can improve health system resilience, care delivery, and equity, particularly in the context of climate-related and access-driven challenges. She combines clinical experience with data-driven approaches to strengthen health systems in an era of rapid digital transformation. Chethan Sarabu, MD, FAMIA, FAAP Dr. Sarabu is Director of Clinical Innovation at Cornell Tech’s Health Tech Hub and Clinical Assistant Professor of Pediatrics at Weill Cornell Medicine and Stanford. His work bridges clinical informatics, design, and sustainability to guide the responsible development of digital health and AI tools. A co-founder of the Climate Health Innovation and Learning Lab, he focuses on aligning emerging technologies with patient experience, environmental stewardship, and system value. Udit Gupta, PhD Dr. Gupta is an Assistant Professor of Electrical and Computer Engineering at Cornell Tech and Cornell Engineering. His research focuses on building sustainable computing systems that reduce the energy, carbon, and material costs of artificial intelligence and data infrastructure. A leader in computer architecture and systems sustainability, he has developed tools and frameworks to quantify and mitigate the environmental footprint of large-scale AI, supported by NSF and industry collaborations. Shomit Ghose Shomit Ghose is a Partner at Clearvision Ventures, a Silicon Valley venture capital fund. He has been a VC since 2001, prior to which he was a start-up entrepreneur for 19 years, serving in all roles from engineer to CEO, and participating in multiple successful start-up exits. Shomit has held a faculty appointment at UC Berkeley’s College of Engineering and an adjunct professor appointment at the University of San Francisco since 2018. He received his degree in computer science from UC Berkeley. Vivian S. Lee, MD, PhD, MBA Dr. Lee is an Executive Fellow at Harvard Business School and Senior Lecturer at Harvard Medical School. Formerly President of Health Platforms at Verily (Alphabet) and CEO of University of Utah Health, she is a physician, scientist, and health system leader recognized for advancing data-driven transformation in healthcare. Her work focuses on improving quality, equity, and sustainability through innovation in health delivery and policy.