[CFAR Distinguished Professor Lecture Series]
Trustworthy Machine Learning (ML) for Healthcare (Hybrid event) by Prof Finale Doshi-Velez
28 Feb 2023 | 9.00am (Singapore Time)
In many healthcare settings, recommendations on new treatment policies based on data from the current practice only. Despite many potential benefits of using prior data to improve future treatments, it is particularly challenging to apply machine learning in healthcare due to the low data quality and high levels of missingness in health data.
In this talk, Prof Finale Doshi-Velez will first describe some machine learning (ML) algorithms that her team has developed for healthcare settings, with applications to decision-making for HIV treatments and in the intensive care unit (ICU). Next, she will also share the work done to validate their algorithms. While statistical checks are necessary to improve methods for off-policy evaluation, they are not sufficient. Prof Doshi-Velez will then introduce the ways of how various kinds of transparency have been incorporated for human experts to apply their domain knowledge and identify potential concerns. She will conclude the talk by describing some of their user studies that demonstrate how ML recommendations could lead people astray and the measures to resolve these issues.
Prof Finale Doshi-Velez is a Gordon McKay Professor in Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). She obtained her MSc from the University of Cambridge as a Marshall Scholar and PhD from the Massachusetts Institute of Technology (MIT). Prof Doshi-Velez completed her postdoc at Harvard Medical School. Her interests lie at the intersection of machine learning, healthcare and interpretability.