New machine learning models to identify driver mutations for clonal hematopoiesis
Our latest work to identify mutations that drive clonal hematopoiesis (CH) has been published in the journal Cancer Discovery.
We developed machine learning models to identify the mutations responsible for CH, an age-related blood condition that increases the risk of developing serious conditions such as blood cancers and cardiovascular diseases. Our work demonstrates the potential of data-driven approaches to support the identification of CH cases in the clinic.