FIT: a Fast and Accurate Framework for Solving Medical Inquiring and Diagnosing Tasks
@article{He2020FITAF, title={FIT: a Fast and Accurate Framework for Solving Medical Inquiring and Diagnosing Tasks}, author={Weijie He and Xiaohao Mao and Chao Ma and Jos{\'e} Miguel Hern{\'a}ndez-Lobato and Ting Chen}, journal={ArXiv}, year={2020}, volume={abs/2012.01065} }
Automatic self-diagnosis provides low-cost and accessible healthcare via an agent that queries the patient and makes predictions about possible diseases. From a machine learning perspective, symptom-based self-diagnosis can be viewed as a sequential feature selection and classification problem. Reinforcement learning methods have shown good performance in this task but often suffer from large search spaces and costly training. To address these problems, we propose a competitive framework…
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