https://scholars.lib.ntu.edu.tw/handle/123456789/581363
標題: | Refuel: Exploring sparse features in deep reinforcement learning for fast disease diagnosis | 作者: | Peng Y.-S Tang K.-F Chang E.Y HSUAN-TIEN LIN |
關鍵字: | Diagnosis; Machine learning; Reinforcement learning; Disease diagnosis; High probability; Reinforcement learning method; Sparse features; Deep learning | 公開日期: | 2018 | 卷: | 2018-December | 起(迄)頁: | 7322-7331 | 來源出版物: | Advances in Neural Information Processing Systems | 摘要: | This paper proposes REFUEL, a reinforcement learning method with two techniques: reward shaping and feature rebuilding, to improve the performance of online symptom checking for disease diagnosis. Reward shaping can guide the search of policy towards better directions. Feature rebuilding can guide the agent to learn correlations between features. Together, they can find symptom queries that can yield positive responses from a patient with high probability. Experimental results justify that the two techniques in REFUEL allow the symptom checker to identify the disease more rapidly and accurately. ? 2018 Curran Associates Inc.All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062170858&partnerID=40&md5=255e840e09007767f2abab5f8c2bf8fd https://scholars.lib.ntu.edu.tw/handle/123456789/581363 |
ISSN: | 10495258 |
顯示於: | 資訊工程學系 |
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