Leveraging Medical Visual Question Answering with Supporting Facts

IBM Research AI (Almaden) team’s participation in the ImageCLEF 2019 VQA-Med competition . The challenge consists of four question-answering tasks based on radiology images . The diversity of imaging modalities, organs and disease types combined with a small imbalanced training set made this a highly complex problem . IBM’s model called Supporting Facts Network (SFN) is to cross-utilize information from upstream tasks to improve accuracy on harder downstream ones . This approach significantly improved the scores achieved in the validation set (18 point improvement in F-1 score). Finally, we submitted four runs to the competition and were ranked seventh .

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Keywords : facts - competition - supporting - ibm - tasks -

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