Training like Playing: A Reinforcement Learning And Knowledge Graph-based framework for building Automatic Consultation System in Medical Field
- Sinohealth research institution（中康科技研究院）
- School of Politics and Public Administration, South China Normal University（华南师范大学政治与公共管理学院）
- Shenyang institute of computing technology, Chinese academy of sciences（中国科学院沈阳计算技术研究所）
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英文摘要：
We introduce a framework for AI-based medical consultation system with knowledge graph embedding and reinforcement learning components and its implement. Our implement of this framework leverages knowledge organized as a graph to have diagnosis according to evidence collected from patients recurrently and dynamically. According to experiment we designed for evaluating its performance, it archives a good result. More importantly, for getting better performance, researchers can implement it on this framework based on their innovative ideas, well designed experiments and even clinical trials.
