Fraunhofer SCAI hat dies direkt geteilt
🌟 Highlights from the University of Oxford Machine Learning Summer School on Health & Bio OxML🌟 Returning from a week filled with cutting-edge insights and thought-provoking discussions led by leaders in the field of AI for health, I put together some key takeaways and insights: 💡 Mihaela van der Schaar (University of Cambridge): Synthetic Data - Powerful Creation, Not Second Rate Copy - The Case for Reality-Centric AI: ML models should be trained & tested considering the "messy", real-world data they will have to deal with at deployment! - Synthetic Data: Essential for managing complex, evolving medical data and generating fair data from biased data. - Debiasing Synthetic Data: Crucial to prevent biased downstream models. ⌚ Tanzeem Choudhury (Cornwell University): Machine Learning and Actionable Sensing for Mental Health - Utilise patient-generated data and traditional healthcare data across disease conditions: A unified data and reasoning platform is needed. - Future of healthcare could be smartphone-centric, integrating diagnostics, therapeutics, and medication delivery, with hospitals for surgeries and some diagnostics. - Adoption moves at the speed of trust. 🔍 Patrick Schwab (GSK): AI assistants for accelerating biological discovery - Compare against biological plausibility and statistical evidence in network inference from mixed observational and interventional data at single-cell scale. - Address cell-type specificity and time-dependence for biological plausibility. Improve models to better estimate "what if?" outcomes. I gained many valuable insights during the summer school and went back home with lots of new ideas to apply in my own research. I'm very grateful for this unique opportunity and all the inspiring and lovely people I've met throughout. A great thanks to the organisers and speakers for such an outstanding experience! #MachineLearning #AI #SyntheticData #OxfordUniversity #RealityCentricAI #HealthcareInnovation