Abstract: Osteoarthritis (OA) is the most common musculoskeletal disease that has no cure. The only available treatment for the end-stage of the disease is total joint replacement, and costs billions of dollars worldwide to manage direct and indirect costs of OA. One of the biggest challenges in OA is a very long time for disease development, which makes the drug development cycle very slow. Large observational cohorts like Osteoarthritis Initiative and Multicenter Osteoarthritis studies have been the gold standard datasets to study knee Osteoarthritis — the most common form of OA, yet we still lack understanding of OA phenotypes and reliable clinical endpoint. During the last 7 years, I got a privilege to be a part of a large community that focused on building tools for accelerating OA research. In my talk, I will specifically focus on machine learning methods that I and my colleagues have developed.
Biosketch: Dr. Aleksei Tiulpin, PhD (title of docent) is an Assistant Professor (tenure track) of Intelligent Medical Systems at the University of Oulu and a Visiting Professor at Aalto University, Finland. He earned his PhD (with distinction) from the University of Oulu in 2020, and later did his postdoc at KU Leuven and Aalto University. In 2022 he obtain his habilitation in machine learning (ML) for medical imaging. Dr. Tiulpin studies the question of using ML to help humans make better decisions in medical applications. He published over 40 scientific peer-reviewed publications that feature the use of ML in musculoskeletal disorders, cancer, dementia, ophthalmology. Dr. Tiulpin published multiple theoretical contributions in machine learning and computer vision in venues like MICCAI, AISTATS, IEEE TMI, PNAS, and Nature Methods.
