B 324 Machine Learning for Genomics and Health

Recent progress in machine learning and artificial intelligence is currently transforming genomics, translational medical research, healthcare, and wellness. Huge data-sets are produced at an increasing rate. This include recordings of smart living augmented by sensor devices, medical images, text data in healthcare and social media, and genomics profiling of a range of different biomolecular data. Concurrent with these developments there has over the last 5 years been a stunning production of open source machine learning tools and powerful computational platforms. These advances are currently advancing bioinformatics, computational biology, systems biology, where an area which could be referred to as Digital Medicine in a broad sense is emerging. We expect students with a background in computer science, mathematics, bioscience, and engineering to learn how to use, develop, and to think on how to use ML/AI techniques in what can broadly be referred to as Digital Technologies for Medicine and Health.