Artificial Intelligence in Clinical and Preclinical Settings
Can AI revolutionize medical practice?
Currently, advances in artificial intelligence (AI) – predominantly in machine learning – seem to be changing different areas of medicine almost on a daily basis. Wherever sufficient data is available, AI systems can learn to classify images or signals, to recognize clinically relevant events, to predict the outcome after incidents or medical intervention or otherwise find novel patterns that are relevant to physicians.
The Section for Artificial Intelligence & Decision Support (AID) at the Medical University of Vienna, emerging from two renowned previous institutes, has performed basic and applied research in AI and machine learning for more than 30 years. Based on several successful collaborations with clinical and pre-clinical research groups, the AID is offering its expertise to all such institutions at the Medical University and beyond, while also cooperating with other AI centers of excellence.
This symposium thus serves a two-fold purpose:
- Several applications of AI in clinical medicine and biology will be presented, providing examples for other potential research partners as to what AI can achieve
- Based on position statements by the collaborating clinicians and life scientists the potentials of AI in various medical fields will be discussed, and questions on how much AI medicine really needs, and what the limitations of such systems are, will be addressed.
14:05 Introduction: Artificial Intelligence at AID and Beyond Georg Dorffner, AID
14:25 Invited Talk: Identifying Predictive Image Patterns for Disease Course and Treatment Response Georg Langs, Dept. of Biomedical Imaging and Image-guided Therapy
14:50 Case Study 1: Diagnosing Cardiac Amyloidosis based on MRI Diana Bonderman, Dept. of Medicine II Asan Agibetov, AID
15:15 Case Study 2: Predictive modelling using DNA methylation Thomas Mohr, Inst. Of Cancer Research Alexander Tolios, Dept. of Blood Group Serology and Transfusion Medicine
15:40 Coffee Break
16:00 Case Study 3: Deep learning for nuclei segmentation: towards a robust method for microscopic tissue analysis Isabella Ellinger, Institute of Pathophysiology and Allergy Research Amirreza Mahbod, TissueGnostics and AID
16:25 Case Study 4: Predicting Relapse in Hyperthyroidism Wolfgang Raber, Dept. of Medicine III Georg Dorffner, AID
16:50 Invited Talk AI in the Eye Ursula Schmidt-Erfurth, Dept. of Ophthalmology and Optometry
17:15 From Data to Knowledge to Cure Matthias Samwald, AID
17:40 Wrap up and General discussion
18:00 Buffet and networking
Also visit our website: meduniwien.ac.at/ai
Part of this research is a contribution to our research focus “Data Science for Personalized Medicine” (cemsiis.meduniwien.ac.at/ds4pm/)
Everyone interested in following the progress of AI in medicine is cordially invited.
Please register until November 5 by sending an email to firstname.lastname@example.org.