AI in imaging for biomedical research

The AI Council at the Faculty of Medicine and TAIGA invite you to a one-day workshop with lectures and basic hands-on training in Application of AI in Imaging Analysis

This short education program and workshop are open to preclinical and clinical researchers, teachers, and students at the Faculty of Medicine. This is at the Introduction level; no specific AI background is needed from the participants.

You will learn the basic concepts of machine learning, deep Neural Networks. The assigning of input images from the images taken by the camera to the radiological images of the tissues from patients.

You will learn by hands-on practice on how AI-models are developed to make our research and clinical work more efficient and simpler.

Lectures 10.00–12:00

Fehmi Ben Abdesslem: AI in medical imaging

Hao Chi Kiang: Deep Learning from Statistical Perspective

Place:  SAM A. 391 in Samhällsvetarhuset

For those only joining the lecturers: https://umu.zoom.us/j/67254417517

Workshop 13.00–16:00

Learn how to apply AI in medical imaging.
at SAM A 391, in Samhällsvetarhuset. There are no requirement of previous knowledge in programming.

Register at this link, no later than November 10
Remember to bring your own computers.

https://forms.office.com/e/kLQvAtj0Vn

Fehmi Ben Abdesslem, Department of Computer Science of Research Institute of Sweden (RISE) and Karolinska Institute, Stockholm. PhD. Senior Research Scientist. He spent several years as a Postdoctoral Fellow at the University of St Andrews in Scotland, and at the University of Cambridge in England. He was then awarded an Alain Bensoussan Fellowship by the European Commission to pursue AI research in Sweden and later offered a permanent position at RISE. He is now also affiliated with Karolinska Institute in Stockholm and UCL in London, as well as employed by Region Stockholm and works closely with Karolinska hospitals in Stockholm. His research includes bringing different AI machine learning methods to the medical field, such as genomics, psychiatry, and cancer research.

Hao Chi Kiang is a statistician with a machine learning and computer science background, currently working toward his doctoral degree in Sweden. In the past decade, he hopped from web development to machine learning, then to statistics; his life keeps getting mathier for some reasons, as he finds himself working in various international settings. Hao Chi Kiang plans to finish his doctoral studies in early 2025.