II. INTERNATIONAL ARTIFICIAL INTELLIGENCE HEALTH CONGRESS
We are pleased to announce that our studies “A Deep Reinforcement Learning Approach to Explore Optimal Policies for COVID-19 Pandemic Mitigation: Preliminary Analysis”, “Unfairness of Deep Learning Methods Arising Gender Bias in COVID-19 Diagnosis of Medical Images” and “Towards Federated Learning in Prediction of Medical Images: A Case Study” are accepted to International Artificial Intelligence in Health Congress, which held between Apr 16 and Apr 18. [...]
