Inquire and Diagnose : Neural Symptom Checking Ensemble using Deep Reinforcement Learning

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Reinforcement Learning in Healthcare: A Survey (2019, background): “Tang et al. [216] formulated inquiry and diagnosis policies as an MDP and adopted DQN to learn to inquire and diagnose based on limited patient data.”
Context-Aware Symptom Checking for Disease Diagnosis Using Hierarchical Reinforcement Learning (2018, methodology): “Table 4: Experimental results on anatomical model (Tang et al. 2016) and our proposed hierarchical model.”
Ensemble deep learning: A review (2021, methodology): “The proposed model in [164] consists of several sub-models which are in response to different anatomical parts.”
Artificial Intelligence in XPRIZE DeepQ Tricorder (2017, methodology): “We have further enhanced the symptom checker module in the DeepQ kit and proposed CASC, which stands for Context-Aware Symptom Checker [25, 26].”
A Berkeley View of Systems Challenges for AI (2017, unknown): “Noteworthy recent results also include Google’s AlphaGo beating the Go world champion [95], and new applications in medical diagnosis [104] and resource management [33].”
Task-oriented Dialogue System for Automatic Diagnosis (2018, background): “In addition, there are two works where deep reinforcement learning is applied for automatic diagnosis (Tang et al., 2016; Kao et al., 2018).”