Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

High-throughput screening (HTS) generates data at a scale that fundamentally shapes the analytical choices available to drug discovery teams. The field of AI vs statistical screening has moved from an ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Research into statistical learning, the ability to learn structured patterns in the environment, faces a theory crisis. Specifically, three challenges must be addressed: a lack of robust phenomena to ...

As artificial intelligence continues to reshape biomedical research, data-driven methods are opening new possibilities for understanding complex inflammatory ...

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human ...