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Curtis Langlotz
Curtis P. Langlotz, MD, PhD, is a prominent figure in the field of medical imaging and artificial intelligence. He serves as the Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center) at Stanford University School of Medicine. Dr. Langlotz is also a Professor of Radiology, Medicine, and Biomedical Data Science at Stanford University and holds the position of Senior Associate Vice Provost for Research. Additionally, he is a Senior Fellow at Stanford’s Institute for Human-Centered Artificial Intelligence and Associate Director of the Institute for Human-Centered Artificial Intelligence (HAI).125
Dr. Langlotz received his undergraduate degree in Human Biology, Master’s in Computer Science, MD in Medicine, and PhD in Medical Information Science from Stanford University. He completed his internship and radiology residency at the University of Pennsylvania.15 Before joining Stanford in 2014, he was on the faculty at the University of Pennsylvania for 20 years.1
Dr. Langlotz is renowned for his contributions to imaging informatics and clinical communication. He has led numerous initiatives, including the development of the RadLex terminology standard and the RSNA imaging AI certificate program.13 He is also a prolific author, having published over 200 scholarly articles and written the book "The Radiology Report: A Guide to Thoughtful Communication for Radiologists and Other Medical Professionals".56
Currently, Dr. Langlotz serves as the President of the Radiological Society of North America (RSNA) and has been a member of its Board of Directors since 2016.15 His research focuses on using deep neural networks and machine learning technologies to enhance disease detection and reduce diagnostic errors.45 On LinkedIn, his username is "langlotz".7
Highlights
"GPT-4V performs similar to physicians on multi-choice accuracy and performs well when physicians answer incorrectly, but frequently gives flawed rationales, most prominent in image comprehension, emphasizing the need for evaluation of its rationales." https://lnkd.in/dDQTMA_v
Truth: "State of the art LLMs don't accurately diagnose patients (performing worse than physicians), don't follow guidelines, cannot interpret lab results, fail to follow instructions, and are sensitive to both the quantity and order of information."
