{"title":"基于CBR的智能头痛诊断模型构建","authors":"Kuan-Wei Huang, Chien-Hua Wang","doi":"10.1145/3507971.3507978","DOIUrl":null,"url":null,"abstract":"∗Recently research found that the probability of having headache between female and male, female that have headache is usually higher than male. Also, headache will get the lower productivity when people working. Therefore, headache is what we called modern disease(s). The purpose of this study is to establish the intelligence headache diagnosis model by using Case Based Reasoning (CBR) to diagnose the probability of the kind of headache and to recommend the doctor regimens on headache patients. The proposed intelligence diagnosis model accuracy rate is 70% above that can be of the great assistance reducing diagnostic errors and improving the medical treatment quality.","PeriodicalId":439757,"journal":{"name":"Proceedings of the 7th International Conference on Communication and Information Processing","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Constructing the Intelligence Headache Diagnosis Model by CBR\",\"authors\":\"Kuan-Wei Huang, Chien-Hua Wang\",\"doi\":\"10.1145/3507971.3507978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"∗Recently research found that the probability of having headache between female and male, female that have headache is usually higher than male. Also, headache will get the lower productivity when people working. Therefore, headache is what we called modern disease(s). The purpose of this study is to establish the intelligence headache diagnosis model by using Case Based Reasoning (CBR) to diagnose the probability of the kind of headache and to recommend the doctor regimens on headache patients. The proposed intelligence diagnosis model accuracy rate is 70% above that can be of the great assistance reducing diagnostic errors and improving the medical treatment quality.\",\"PeriodicalId\":439757,\"journal\":{\"name\":\"Proceedings of the 7th International Conference on Communication and Information Processing\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 7th International Conference on Communication and Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3507971.3507978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 7th International Conference on Communication and Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3507971.3507978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
*最近的研究发现,女性和男性之间有头痛的可能性,女性头痛通常高于男性。此外,头痛会降低人们工作的效率。因此,头痛是我们所说的现代疾病。本研究的目的是利用基于案例推理(Case Based Reasoning, CBR)的方法,建立智能头痛诊断模型,以诊断头痛类型的概率,并为头痛患者推荐医生治疗方案。所提出的智能诊断模型准确率在70%以上,对减少诊断错误、提高医疗质量有很大帮助。
Constructing the Intelligence Headache Diagnosis Model by CBR
∗Recently research found that the probability of having headache between female and male, female that have headache is usually higher than male. Also, headache will get the lower productivity when people working. Therefore, headache is what we called modern disease(s). The purpose of this study is to establish the intelligence headache diagnosis model by using Case Based Reasoning (CBR) to diagnose the probability of the kind of headache and to recommend the doctor regimens on headache patients. The proposed intelligence diagnosis model accuracy rate is 70% above that can be of the great assistance reducing diagnostic errors and improving the medical treatment quality.