Winners of the ImageCLEF 2020 Medical VQA Challenge

Congratulations to Zhibin Liao and team for winning the ImageCLEF 2020 Medical VQA challenge.

The global Medical Visual Question Answering (VQA) Challenge tests participants to design an automated visual question answering system that analyses a radiology image and answers user questions, such as describing what is showing in the image and what pathologies can be seen.

Such systems can give clinicians a "second opinion" and also gives patients an additional interpretation of their own radiology exam images.

Zhibin and team trained their own VQA model on the dataset provided by the challenge and then applied several machine learning and NLP techniques to improve the accuracy and robustness of the model.

Congratulations to the team for taking out first place!

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