![]() |
COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. | ![]() |
University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Model Evaluations under Uncertain Ground Truth
![]() Model Evaluations under Uncertain Ground TruthAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact nobody. OFBW74 - Uncertainty in Machine Learning: Challenges and Opportunities AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is often assumed to be fixed and certain. However, in many domains, such as medical applications, the ground truth is often curated in the form of differential diagnoses provided by multiple experts. While a single differential diagnosis reflects the uncertainty in one expert assessment, multiple experts introduce another layer of uncertainty through potential disagreement. In this talk, I will argue that ignoring uncertainty leads to overly optimistic estimates of model performance, therefore underestimating risk associated with particular diagnostic decisions, leading to unanticipated failure modes. We propose a statistical aggregation approach, where we infer a distribution on probabilities of underlying medical condition candidates themselves, based on observed annotations. This formulation naturally accounts for the potential disagreements between different experts, as well as uncertainty stemming from individual differential diagnoses, capturing the entire ground truth uncertainty. We conclude that, while assuming a crisp ground truth can be acceptable for many AI applications, a more nuanced evaluation protocol should be utilized in medical diagnosis. If time permits, I will also cover some work, based on conformal methods that can provide statistical guarantees. Based on joint work with David Stutz, Melih Barsbey, Alan Karthikesalingam, Arnaud Doucet and many others This talk is part of the Isaac Newton Institute Seminar Series series. This talk is included in these lists:
Note that ex-directory lists are not shown. |
Other listsLet count in Sustainable Development: 11th Distinguished Lecture Series 2013 The obesity epidemic: Discussing the global health crisisOther talksExternal Seminar - Lars Østergaard TBC GPU Accelerated Nested Sampling ‘Unpicking the biology of healthy human nasal microbiome’ Science advice under uncertainty Bayesian Inference Tutorial When fire plumes glow in the dark: Tracing organic aerosol chemical regime dominance clues via light-absorbing species |