Master of Health Science in Medical Artificial Intelligence

I have twenty five plus years of experience in medical image analysis, machine learning, and software development. I have been involved in a variety of imaging projects ranging from cardiac image analysis, image-guided epilepsy neurosurgery, image-guided prostate biopsy, development of methods for real-time fMRI, vascular image analysis and general neuroimaging analysis. We have used both model-based approaches (biomechanical and physiological models) and more data-driven statistical/machine learning approaches. These projects spanned most of the imaging modalities (MRI, CT, Ultrasound, PET, SPECT, Optical), body parts (brain, head, heart, vasculature, prostate, abdomen, hindlimbs) and a variety of species. In addition to algorithm research, I have been heavily involved in the development of medical image analysis software. My software work (which is directly linked to the image analysis research) has focused on the creation of tools for image analysis both at Yale and as a consultant for industry. My early work (1990s) used C++/Motif/OpenInventor on Silicon Graphics workstations. Later I used C++/Tcl/VTK as part of the creation of the original Yale BioImage Suite software package. More recently, I have focused on the creation of web-based tools using a combination of JS and C++ (via WebAssembly) to create server-less tools that can be run in a browser. Some of the C++ algorithms are also made available for use in Python and MATLAB scripts. In addition to actual software development, I teach a class on Medical Software at Yale which formed the basis for our recently released textbook “Introduction to Medical Software: Foundations for Digital Health, Devices and Diagnostics” that was just published by Cambridge University Press (Summer 2022) and a Coursera online class titled “Introduction to Medical Software” that was released in October of 2021 and which currently has more than 26000 enrolled students from all over the world. I also direct the Yale Certificate Program in Medical Software and Medical AI. Finally, I am a member of a number of technical standards committees at the Association for the Advancement of Medical Instrumentation (AAMI) on software and artificial intelligence. Full Biography

Allen Hsiao MD, FAAP, FAMIA, is Professor of Pediatrics, Biomedical Informatics and Data Science, and of Emergency Medicine at the Yale School of Medicine and serves as the Chief Health Information Officer (CHIO) for the Yale School of Medicine and Yale New Haven Health System. Dr. Hsiao also serves as the Vice Chair Clinical Systems, Biomedical Informatics and Data Science. He received his BA in Biomedical Ethics and MD from Brown University, then completed residency training in Pediatrics at Yale before completing fellowships and board certifications in Pediatric Emergency Medicine and Medical Informatics. He has served on numerous medical informatics-related committees for the Hospital and University, as well as nationally for groups such as the American Academy of Pediatrics, Health Information Management Systems Society, and the National Association of Children’s Hospitals and Related Institutions. Dr. Hsiao has published many articles in the pediatric and healthcare informatics literature and regularly presents nationally and internationally on leveraging informatics and the electronic health record (EHR) to support research, optimize systems, and improve transitions of care. He has also served as primary investigator or co-investigator on several NIH and AHRQ-funded grants examining the ways health information technology can impact and improve healthcare. Dr. Hsiao also co-directs the Informatics Core for Yale’s Clinical Translational Science Award (CTSA) from the National Institutes of Health. In this capacity, he works closely with the Yale Center for Clinical Investigations leadership to equip investigators with the tools and information needed for translational and clinical research. This includes leveraging the industry-leading functionalities of the EHR (Epic) system and the clinical trials management system (OnCore) for investigators and patient focused research, with particular emphasis on expanding clinical trials participation by patients from diverse backgrounds to improve health equity and inclusion in clinical research. As the CHIO, Dr. Hsiao leads the medical and clinical informatics work for the Health System and School of Medicine Full Biography