How Can AI Models Change Biomedical Discovery?
To Know
About this Class
Today, major breakthroughs in understanding disease biology and developing treatments require significant wet lab exploration. Emerging AI algorithms for Electronic Health Records (EHR), image processing, and molecular modeling can potentially provide an alternative means for exploring a large space of possible solutions, enabling scientists to prioritize the most promising hypotheses for testing. These developments have significant implications for data management, curation, and stewardship. In this talk, the speaker will describe several examples illustrating the power and weaknesses of current AI technology in today’s data landscape. In the second half of the talk, she will focus on the impact of training data on the performance of AI models in this discovery context and on the ethics and reproducibility considerations.