Explainable AI for Biology

The application of A.I in biology and medicine is becoming ubiquitous. The near superhuman accuracies achieved by A.I algorithms can be attributed to A.I’s ability to find patterns in multi-dimensional
(multi-factorial) datasets - generally a very challenging and labour-intensive task for humans. Hence, it is imperative for a field such as biology and medicine, where the output of A.I algorithms affect the health and well-being of individuals, that results are explainable and reproducible. Our group is developing new mathematical methods to help understand the results of AI-based algorithms in the context of Biology. We are a mixed group of Wet-lab (Biologists) and Dry-lab (Mathematicians), working together on understanding and remedying diseases through explainable A.I.