1 week. 10 experts.
Re-think medicine of tomorrow
as part of an interdisciplinary team.
When it comes to medicine, Artificial intelligence (AI) is indispensable. AI facilitates prognoses that even the most advanced medicine is not capable of. Scientific AI models, for example, literally look into the future, predicting a life-threatening decline in a patient's condition 15 minutes before it might even happen and before the patient even feels any symptoms or notices any signs. This can facilitate effective intervention long before a problem occurs, resulting in saving patients' lives.
In support of modern healthcare, AI utilizes collected patient data and supports the decision-making process, thereby creating visionary new methods of treatment and opportunities to forge new paths.
Together with students in various academic disciplines, we aim to not only think beyond the status quo of what has been possible thus far, but also engage in visionary questions at the crosroads of AI and medicine.
What can AI do for medicine? How can medicine draw on AI and look forward?
What legal/social/ethical issues need to be taken into consideration?
What are some of the potential AI implications in regard to making medical decisions?
This course aims to expand on perspectives extending beyond one's own area of expertise, find common ground to explore innovative solutions, ask tough questions at the crossroads of AI and medicine, and "think outside of the box", so to say. Students will work as part of an interdisciplinary team to address questions and case studies. Experts from Austria and abroad have been invited to speak, hold workshops, and provide feedback. The various concepts will be presented at the Circus of Knowledge on October 5.
AI in Medicine. Potential, Challenges and Perspectives for the Future
September 26 - 30 &
October 5, 2022
A one-week course about the Future of AI & Medicine.
(2 semester hours)
WHO IS ELIGIBLE TO TAKE PART
Undergraduate students (fifth semester and up), graduate and PhD students at the Faculty of Engineering & Natural Sciences, the Faculty of Medicine, and other interested students in law and business
German (some presentations will be held in English)
The course can count for up to 2 ECTS credits toward elective or autonomous coursework