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Explainable AI

Deep learning methods alone do not reflect actual reasoning behind decisions due to highly parametric solutions thus are hard to comprehend and trust for clinicians. Recent explainable Artificial Intelligence (xAI) research has provided real world applications with numerous techniques to make deep learning models more transparent and understandable by unveiling their decision/prediction making processes. We have few separate projects to analyze our deep learning models’ predictions and behaviour with various xAI methods.


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