Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI)

Join us for the 4th annual Stanford AI+HEALTH Conference, held online on Dec. 10-11, where we'll dive into real-world AI innovations and applications across healthcare. This year's program builds on the insights of thousands of past attendees and is designed to be practical and impactful, delivering actionable knowledge that connects AI innovations with clinical practice. Whether you're a clinician, researcher, innovator, or professional from academia, industry, government, or the non-profit sector, this conference offers valuable opportunities to connect, learn, and explore — wherever you are in your AI journey. Register today: aiplushealth.stanford.edu ✨ Special Offer: The first 100 registrants receive the best conference rate! Early registration ends October 31, 2024. Hosted by the AIMI Center, Stanford Institute for Human-Centered Artificial Intelligence (HAI), and Stanford CME #AIplushealth24 #AIInHealth #HealthInnovation #ArtificialIntelligence #AIMICenter #DigitalHealth #HealthTech #FutureOfHealthcare

We're excited to share a new publication that highlights the establishment and journey of the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI Center) over the past six years. Published in Mayo Clinic Proceedings: Digital Health, the paper details how we created an interdisciplinary center to address clinically significant questions with AI/ML, fostering collaboration among clinicians, data scientists, and computer scientists to tackle complex biomedical challenges. The publication outlines four core pillars that have guided our efforts: - Building a vibrant interdisciplinary community - Catalyzing extramural funding through internal grant programs - Developing infrastructure to enable large-scale, AI-ready clinical datasets - Engaging and educating the broader research community It also reflects on lessons learned and previews what's ahead as we continue to advance the role of AI in healthcare. We invite you to read the full text and learn more about our center's journey: https://bit.ly/4hZr92h We are deeply grateful to the broader AI in health and medicine community for your support and partnership in transforming medicine with AI. Special thanks to everyone who has contributed to this journey, especially: Curtis Langlotz, Johanna Kim, Nigam Shah, Matthew Lungren MD MPH, David Larson, Somalee Datta, Fei-Fei Li, Ruth O Hara, Thomas Montine, Robert A. Harrington, Garry Gold, Stanford Radiology, Stanford University School of Medicine, Stanford Department of Medicine, Stanford Medicine: Department of Pathology #StanfordAIMI #AIinHealthcare #HealthTech #FutureOfMedicine #ResponsibleAI

What an incredible turnout for the AIMI Fall Open House! We're thrilled to see the AI in health community at Stanford continuing to grow and thrive. It was inspiring to connect with so many passionate individuals—from fresh faces to longtime collaborators—all dedicated to advancing the field together. The event highlighted opportunities to engage through AIMI's funding programs, open data sharing, educational initiatives, and our industry collaborations. A special highlight was the presentation from AIMI- Stanford Institute for Human-Centered Artificial Intelligence (HAI) partnership grantee Keith Morse, who shared insights into his innovative pediatric AI research supported by the program. Conversations throughout the event including dynamic networking sessions, underscored the strength of this community. Thank you to everyone who joined us to build this shared vision. Missed this one? We'll be hosting another Open House next quarter and look forward to seeing you there! #StanfordAIMI #AIHealthCommunity #TeamScience

TL;DR -- If you're passionate about working at the intersection of building models, verifying benefits and responsible deployments, join us in bringing AI into routine clinical use safely, ethically, and cost-effectively. Apply directly via -- https://lnkd.in/gmnKv-GU. Read on for more context ... (and share widely!) In 2022, we launched a new team (https://lnkd.in/gcV6RqTe) in Technology & Digital Solutions - Stanford Medicine to harness artificial intelligence to support and enhance every aspect of health care delivery, AI research and medical education. This team works closely with multiple faculty and students in the Stanford Department of Medicine, Stanford Biomedical Data Science Program, Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI), Stanford CERC for research on AI for Cost-effective, Accurate, Reliable, and Ethical Solutions (AI-Care). We have worked on how to build Fair, Useful, Reliable Models (FURM -- https://lnkd.in/gM49mqXf), shape the adoption of LLMs in medicine (https://lnkd.in/g6vCyqhC) and their evaluation (https://lnkd.in/gnSVYa-9). We share our learning via a uniquely Stanford take on an AI assurance lab (https://lnkd.in/gwhX4nmM) called GUIDE-AI, for Guidance for the Use, Implementation, Development, and Evaluation of AI. These efforts at Stanford Health Care are tightly synced with research on evaluating clinical benefits (https://lnkd.in/gqidQfdc), building time-aware foundation models (https://lnkd.in/gBkJxtbK), simulating achievable benefits (https://lnkd.in/g5dVvZrS), developing methods for continuous evaluation (https://lnkd.in/gXk7aiZH) and for highlighting the patients' voice (https://lnkd.in/gcYrMrWP). This role of a senior program manager will co-lead and administer activities and programs with me at this interdisciplinary frontier of building models, verifying their benefits and responsible deployments! Join us via https://lnkd.in/gmnKv-GU; apply by Monday, January 13, 2025. Tagging some TDS and faculty colleagues to help share this widely. Sneha Shah Jain, MD, MBA, Jonathan H. Chen, Michelle Mello, Dev Dash, N. Lance Downing, MD, Margaret Smith, Keith Morse, Roxana Daneshjou, Akshay Chaudhari, Johanna Kim, Curtis Langlotz, Nerissa Ambers, Nikesh Kotecha, Anurang Revri, Michael Pfeffer

Join us for our next NextGen Tech Talk on Nov. 4! Stanford physician data scientist Dr. Jonathan H. Chen will share insights on the powerful blend of human and artificial intelligence in healthcare, along with career advice for aspiring minds. Dr. Chen's journey combines deep expertise in data science and clinical practice, offering a unique perspective on today's transformative role of AI in healthcare. From founding an AI-based company to publishing extensively, he brings a wealth of knowledge to inspire the next generation. About AIMI NextGen Tech Talks: This live webinar series is designed for high school students curious about AI's impact in medicine and health. Each session spotlights leaders who are driving change, offering attendees an inspiring look into the paths and possibilities in healthcare through technology. 📅 Event Details: Date: Monday, November 4, 2024 Time: 5:00 - 5:45 PM Pacific Time Format: Live webinar + Q&A Registration: Free, open to all ages! Register here: https://bit.ly/3YunFvE Can't make it? A recording will be available on AIMI's YouTube channel: https://lnkd.in/gGenwiPA #NextGenTechTalk #AIInMedicine #AIInHealth #STEMeducation #FutureofHealth #YouthInSTEM #CareerInspiration

We're delighted to be at Stanford Center for Digital Health (CDH)'s Inaugural Symposium today! Our director Curtis Langlotz and co-director Nigam Shah will be discussing "How do we evaluate the real-world impact of digital interventions?" together with AIMI affiliated faculty Fatima Rodriguez, MD, MPH and Michael Snyder. Livestream: https://bit.ly/3NBPIVd Links to the recording will be posted when available. #CDHSymposium #AIInHealth #FutureOfMedicine #healthtech

Exploring Responsible AI: Impact on Healthcare, Education, and Women Leading the Charge Listen to Alaa Youssef who will be speaking at the upcoming Ai Summit Fall 2024 in an exciting panel session on AI in Healthcare. The panel will focus on Responsible AI, examining how ethical AI policies are shaping education and healthcare, and highlighting the leadership of women in AI. This discussion promises to explore critical insights on the current state of Responsible AI and its impact across industries. Alaa Youssef is a Postdoctoral Scholar at Stanford's Center for Artificial Intelligence in Medicine and Imaging (AIMI). With a passion for responsible AI, Alaa’s work bridges the gap between cutting-edge technical innovation and ethical practice in healthcare. Her research focuses on enhancing patient care through the responsible deployment of AI technologies, driving both academic and practical advancements in the field. Join us at the Fall 2024 Ai Summit—AI for Everyone, where we delve into how democratizing AI can create a more equitable future for all. 🎟️ Register Now at https://lnkd.in/ghdaeF6R 
 📅 Date: October 26th, 2024
 📍 Location: Computer History Museum, Mountain View, CA (or online) #AiSummit2024 #ResponsibleAI #WomenInAI #HealthcareAI #AiForEveryone

Just released: The 2024 RAISE Health Symposium summary paper! This report highlights insights from the May 14 symposium, where experts explored the essential steps needed for AI's successful integration into biomedicine over the next decade and beyond. Alongside the report, we're sharing a quick Q&A with AIMI Center Director Curtis Langlotz, who discusses why this paper is a must-read, notable findings, and what immediate actions can ensure responsible AI deployment in healthcare. 📄 Swipe to read the Q&A and access the full report here: https://stan.md/4f6P6SX Stanford University School of Medicine Stanford Institute for Human-Centered Artificial Intelligence (HAI) Summary Paper Leads: Russ Altman, Sanmi Koyejo, Curt Langlotz, Sylvia Plevritis Working Session Contributors: Hatim Abdulhussein, Alyce Adams, Laura Adams, Brian Anderson, MD, Katya Andresen, Kim Branson, Danton Char, Constance Chu, David Entwistle Declan Grabb, MD, Anika Heavener, Tina Hernandez-Boussard, Sneha Shah Jain, MD, MBA, Katherine Kim, Paul A. King, Vincent Liu, Matthew Lungren MD MPH, Yifan Mai, Sharmila Makhija MD MBA, Karen Matthys, Ryan Merkley, Richard Milani, Kiran Mysore, Michael Pfeffer, Fatima Rodriguez, MD, MPH, Nigam Shah, Priya Singh, Teggin Summers, Tanveer Syeda-Mahmood, Nina Vasan, MD, MBA, Michelle Williams, Maame Yaa "Maya" A. B. Yiadom #RAISEHealth #ResponsibleAI #EthicalAI #HealthAI

In 2023, we (Michael Pfeffer, and David Entwistle) argued in JAMA, Journal of the American Medical Association (https://lnkd.in/gS--Z3Hv) that the use of LLMs in healthcare need to be actively shaped by specifying the desired benefits and evaluating them via testing in the real-world. Today, we follow up with a systematic review of how the testing and evaluation (T&E) of healthcare application of LLMs is done. TL;DR =  current evaluations of LLMs in healthcare are sub-optimal (95% do not use real patient records!). Our future evaluations need to use real patient data, quantify biases, and cover wider categories of tasks and specialties. Paper at https://lnkd.in/gnBNErYJ; a nice summary by Lucy Orr-Ewing at https://lnkd.in/gVNzDqCY; Suhana Bedi, Yutong Liu and co-authors tagged below. The review was a collaboration between Technology & Digital Solutions - Stanford Medicine, and the Coalition for Health AI (CHAI), to inform the ongoing T&E framework for GenAI led by Karandeep Singh and Zachary Lipton. Research to address this evaluation gap, begun with Robert A. Harrington's support at Stanford Department of Medicine, provides an early example of real-world evaluations (https://lnkd.in/gFrVt-43, https://lnkd.in/gnuMmsWn) and continues to thrive with Euan Ashley! Co-authors: Dev Dash, Sanmi Koyejo, Alison Callahan, Jason Fries, Michael Wornow, Akshay Swaminathan, Lisa Lehmann, H. Christy Hong, MD MBA, Mehr Kashyap, Akash Chaurasia, Nirav R. Shah, Karandeep Singh, Troy Tazbaz, Arnold Milstein, Michael Pfeffer. #GenAI #healthcare #LLM

How are AI tools helping radiologists? Stanford University School of Medicine's Dr. Curtis Langlotz discusses how using radiology data could help maximize accuracy, and more with Icahn School of Medicine at Mount Sinai Department of AI and Human Health’s Dr. Robert Hirten MD at the New Wave of AI in Healthcare 2024. Watch the full video here: https://lnkd.in/gcWAkEZB