AI seminar: Research and Development of Medical Imaging Applications in Radiology

Alexandros KARARGYRIS, PhD, will give a webinar, Thursday, December 10, 2020 at 4pm.

Title: Research and Development of Medical Imaging Applications in Radiology

Abstract: Recent developments in Machine Learning, such as Deep Learning, have revolutionized many areas of science and technology, from autonomous cars and agriculture to healthcare. With the ability to harvest large amounts of data, Deep Learning has transformed the space of medical image analysis resulting in an influx of research publications and commercial products. Despite its success, there exist open challenges in the areas of explainability, generability and limited labelled data, thus blocking large and fast adoption of Machine Learning tools in clinical settings.
In this talk I will present my experience in research and development of applications for radiology imaging highlighting these challenges. Specifically, I will discuss my work related to Point-of-Care applications, methods that perform on limited labelled data as well as approaches on Human-Machine synergy that can promote better explainability. Finally, I will discuss how collaborative efforts by academia and industry try to address reproducibility and generability in Machine Learning and accelerate its adoption.

Bio: Dr. Alexandros Karargyris obtained his PhD from Wright State University. For the past 10 years he has worked as a researcher at the National Institutes of Health and IBM Research. His research interests include medical imaging, mobile health and machine learning. He has published more than 60 peer reviewed papers and patents. Currently, he is the Chair for the Medical Accuracy group at MLPerf leading the efforts on Medical Machine Learning benchmarks.

To obtain the access link, please contact us at: contact@icube.unistra.fr.