Webinar: Uncertainty Quantification: A Way Towards Trustworthy Deep Learning In Medical Imaging

Event Organizer: Society for Imaging Informatics in Medicine

Event Website: https://siim.org/webinar/uncertainty-quantification-a-way-towards-trustworthy-deep-learning-in-medical-imaging/

Event Overview:

“In recent years, deep learning has shown impressive performance in medical imaging analysis. However, for a model to be useful in the real world, it needs to be valid and trustworthy. The uncertainty quantification (UQ) methods determine the calibrated level of a model’s confidence in its predictions. Moreover, UQ can demonstrate biases caused by overconfidence or lack of confidence in the model’s predictions. By enabling UQ in medical deep learning models, users can be alerted when a model does not have enough information to make a decision. Consequently, a medical expert could reevaluate the uncertain cases, which would eventually lead to gaining more trust in the model.”

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