Machine learning (ML) has the potential to revolutionize healthcare and biomedicine, but also faces unique challenges in this area. In this seminar, we will examine how ML is solving complex tasks across various biomedical disciplines. Topics range from analyzing microscopic tissue images (computational pathology, multiple instance learning) and mapping cellular environments (single-cell analysis, spatial transcriptomics) to designing novel therapeutics (protein structure prediction, generative drug discovery). We will also tackle critical clinical and ethical challenges, including multimodal AI, algorithmic fairness, and model explainability. Candidates will read, present, and discuss some of the most recent and relevant papers driving the intersection of AI and medicine today. Candidates will read, present, and discuss some of the most recent and relevant papers on ML in computational pathology.
- Trainer/in: Weronika Oktavia Klos