Abstract. Prostate cancer (PCa) is the most common cancer in men and the second leading cause of cancer death in Germany [4,14]. Both digital rectal examination (DRE) along with the prostate-specific antigen (PSA) level in blood samples are typically used in PCa screening.
Machine Learning has gained a lot of momentum within development organizations that are actively looking for innovative solutions to leverage their data to identify new levels of understanding their operations and processes. Machine learning is a subfield of Artificial Intelligence where the machine learns from data rather than from explicit programming.
Organizers: Dr. Shadi Albarqouni, Helmholtz AI and TU Munich, Prof. Nassir Navab, Chair for Computer Aided Medical Procedures, and Prof. Daniel Rueckert, Chair for AI in Medicine, TU Munich
Time: Fridays, 10:00 - 12:00
Organizers: Dr. Shadi Albarqouni, Helmholtz AI and TU Munich, and Prof. Nassir Navab, TU Munich.
Announcements - 17-12-2020: The deadline to submit the blog post is moved to 1st. Feb. 2021.
This 5-day intensive course is tailored for PhD students from diverse disciplines seeking a robust introduction to Artificial Intelligence (AI) and Machine Learning (ML). The module begins with essential mathematical concepts, including algebra, probability, and optimization, before moving into fundamental and advanced machine learning techniques. Students will explore deep learning architectures, engage in hands-on coding exercises, and apply their knowledge to real-world problems, with a particular focus on healthcare and resource-constrained environments. The course also addresses the ethical implications of AI and the importance of explainability in AI models, preparing students to implement AI solutions responsibly in their research.
This 8-week intensive course provides non-computer science students with the essential skills to apply AI in medical diagnosis and prediction. The course covers topics such as medical image classification, detection, segmentation, and reconstruction, as well as time-series classification, regression, forecasting, and learning techniques like weakly-, semi-, and self-supervised learning. Ethical considerations, fairness, and robustness in AI are also highlighted.
Abstract. Diseases of the cardiovascular system are among the most common diseases worldwide and are the leading cause of death. The World Health Organization (WHO) estimates that about 17.9 million people die of cardiovascular diseases each year worldwide.