Events
Research & Guest Speaker Events
Expert-Informed, User-Centric Explanations of Medical Image Classification
We argue that the dominant approach to explainable AI for explaining image classification with deep learning– annotating images with heatmaps, provides little value for users unfamiliar with deep learning. Instead, we argue that explainable AI for images should produce output like experts produce when communicating with one another, with apprentices, and with novices. We discuss a bit of the history of interpretable and explainable AI with examples from AI & medicine. A new approach that labels image regions with diagnostic features is proposed and evaluated. We draw on examples from radiology, ophthalmology, dermatology as well as bird classification.
This virtual event will be held on
Friday, October 4, 2024 at 4:00 PM EST
The clinical outcome of any infectious disease can vary widely, ranging from asymptomatic cases to fatal outcomes, depending on a complex interplay between the pathogen, host, and environment. Traditionally, the study of infectious diseases has focused primarily on the pathogen, which has limited our understanding of the environmental and host-specific factors that influence disease susceptibility and severity. Addressing this gap is crucial for developing effective strategies and treatments for infectious disease control. In this talk, I will present our research on the role of human genetic factors and social determinants of health in infectious disease outcomes. I will also demonstrate how we can harness the power of large-scale biobanks and systems biology approaches to gain deeper insights into the complex mechanisms that determine the clinical outcomes of infectious diseases.
This virtual event will be held on
Friday, November 15, 2024 at 10:00 AM EST
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