基于NLP和模糊逻辑的Android临床诊断应用

Samuel Afoakwa, Crentsil Kwayie, Joseph Owusu
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引用次数: 1

摘要

自然语言处理(NLP)方法在健康诊断会话框架设计中的应用,提高了患者对医疗信息的获取。本研究开发了一个基于模糊逻辑规则和模糊推理的Android应用程序。在加纳,该服务评估疾病的症状。android应用程序使用支持向量机器学习技术构建,旨在提高模型的准确性和性能。机器通常使用自然语言处理来实现询问用户症状的会话风格。通过使用这种主要在加纳农村地区使用的技术,人们可以减少在医院的时间,并获得低成本或免费的护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Android Application for Clinical Diagnosis Using NLP and Fuzzy Logic
The application of natural language processing (NLP) methods to designing conversational frameworks for health diagnosis improves patients’ access to medical information. An Android application based on fuzzy logic rules and fuzzy inference was created in this research. In Ghana, the service assesses the symptoms of diseases. The android application is built with the Support Vector Machine learning technique, with the aim of improving the model’s accuracy and performance. Natural Language Processing is often used by the machine to achieve the conversational style of asking the users for their symptoms. People can spend less time in hospitals and get low-cost or free care by using this technique, which is mainly used in Ghana’s rural areas.
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