The Axe Santé is organising a Health Tech Lunch on Tuesday, October 20th from 12:00 to 12:45 at Swiss Digital Center in Sierre (room Maïa).
Biography : Alexandros Karargyris leads the Medical working group at MLCommons. The group has a mission to provide neutral benchmarking and best practices for Medical AI in an effort to circumvent negative effects of AI. In its short life span the group has grown to already support the largest federation of brain tumor segmentation as well as to plan its prospective AI studies. Previously he worked as a research lead at IHU Strasbourg in projects related to applications in the intersection of surgery and AI. He also worked as a researcher at IBM and NIH for more than 10 years. His research interests lie in the space of medical imaging, machine learning and mobile health. He has contributed to healthcare commercial products and imaging solutions deployed in under-resourced areas. His research has been published in peer-reviewed journals and conferences.
Abstract : AI has shown its potential to impact healthcare in unprecedented ways. However its clinical translation, from research to the real world, is held back by lack of robust validation in diverse patient populations. Repeated stories of AI trained on selected populations but failing in real world scenarios demonstrate gaps in AI/ML (e.g. bias, socioeconomic gaps). In this talk I will be presenting MedPerf (http://medperf.org), an open source platform for reproducible benchmarking of medical AI at global scale to help mitigate some of the current challenges. More specifically, I am going to be discussing current development and future directions of the platform. This is an excellent opportunity to identify common interests and directions with the digital pathology community. MedPerf is developed and maintained on a volunteering basis by a diverse group of industry and academic researchers offering a neutral approach to benchmarking. The platform is supported by MLCommons (http://mlcommons.org), a non-profit technical organization for ML benchmarking supported by industry and academia
Registration : https://doodle.com/meeting/participate/id/b4LBgY2b