一个基于模糊的本体论的基于病例的推理系统,用于波斯医学中的胃
Hassan Shojaee-Mend1, Haleh Ayatollahi2, Azam Abdolahadi3
1Infectious Diseases Research Center, Gonabad University of Medical Sciences, Gonabad, Iran.
PloS one
|October 24, 2024
概括
一个新的基于模糊本体学的基于案例的推理 (CBR) 系统准确地诊断了波斯医学中的胃. 这种方法通过将传统知识与计算方法相结合来提高诊断精度,以获得更好的患者结果.
科学领域:
- 传统的波斯医学是传统的波斯医学.
- 计算智能是一种计算智能.
- 医疗信息学 医疗信息学
背景情况:
- 在波斯医学中,准确诊断胃气对于预防其他疾病至关重要.
- 传统的诊断方法通常依赖于模两可的信息,这给医生带来了挑战.
- 模糊的本体学和基于案例的推理 (CBR) 为提高诊断准确性提供了潜在的解决方案.
研究的目的:
- 在波斯医学框架内开发和评估基于模糊本体学的CBR系统,用于诊断和治疗胃.
- 改进传统诊断标准的结构化表示和计算分析.
主要方法:
- 采用混合方法方法来开发基于模糊本体学的CBR系统.
- 模糊的特征和会员功能 (形,三角形等) 被用来表示语言变量,如饥饿和消化.
- 该IKARUS-Onto方法指导着模糊案例基础本体学的发展,随后是CBR系统的设计和实施.
主要成果:
- 建立了一个基于病例的模糊本体学,并填充了一个数据库,其中包含88个经过专家验证的医疗记录.
- 该系统实现了高性能指标:97.5%的灵敏度,87.5%的特异性,96.6%的精度,98.7%的精度和98.1%的F1分数.
- 最常见的诊断是质性气质变化 (72%),其次是冷干气质变化 (18%).
结论:
- 根据波斯医学原则,开发的基于模糊本体学的CBR系统在诊断胃气方面表现出显著的有效性.
- 该系统有望提高诊断准确性和识别类似病例,可能有助于临床决策.
- 建议在现实世界的临床环境中进一步验证,以确认其实际适用性和实用性.
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