M. Juhola, K. Viikki, J. Laurikkala, Y. Auramo, E. Kentala, I. Pyykkö
{"title":"人工智能在听力学中的应用","authors":"M. Juhola, K. Viikki, J. Laurikkala, Y. Auramo, E. Kentala, I. Pyykkö","doi":"10.1080/010503901300007209","DOIUrl":null,"url":null,"abstract":"In this paper, machine learning methods based on artificial intelligence theory are applied to the computer-aided decision making of some otoneurological diseases, for example Me´nie`re's disease. Three methods explored are decision trees, genetic algorithms and neural networks. By using such a machine learning method, the decision-making program is trained with a representative training set of cases and tested with another set. The machine learning methods are useful also for our otoneurological expert system, One, which is based on a pattern recognition approach. The methods are able to differentiate most of the cases tested between the six diseases included, provided that a sufficiently large training set is available.","PeriodicalId":76516,"journal":{"name":"Scandinavian audiology","volume":"30 1","pages":"97 - 99"},"PeriodicalIF":0.0000,"publicationDate":"2001-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/010503901300007209","citationCount":"2","resultStr":"{\"title\":\"Application of artificial intelligence in audiology\",\"authors\":\"M. Juhola, K. Viikki, J. Laurikkala, Y. Auramo, E. Kentala, I. Pyykkö\",\"doi\":\"10.1080/010503901300007209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, machine learning methods based on artificial intelligence theory are applied to the computer-aided decision making of some otoneurological diseases, for example Me´nie`re's disease. Three methods explored are decision trees, genetic algorithms and neural networks. By using such a machine learning method, the decision-making program is trained with a representative training set of cases and tested with another set. The machine learning methods are useful also for our otoneurological expert system, One, which is based on a pattern recognition approach. The methods are able to differentiate most of the cases tested between the six diseases included, provided that a sufficiently large training set is available.\",\"PeriodicalId\":76516,\"journal\":{\"name\":\"Scandinavian audiology\",\"volume\":\"30 1\",\"pages\":\"97 - 99\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/010503901300007209\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scandinavian audiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/010503901300007209\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scandinavian audiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/010503901300007209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of artificial intelligence in audiology
In this paper, machine learning methods based on artificial intelligence theory are applied to the computer-aided decision making of some otoneurological diseases, for example Me´nie`re's disease. Three methods explored are decision trees, genetic algorithms and neural networks. By using such a machine learning method, the decision-making program is trained with a representative training set of cases and tested with another set. The machine learning methods are useful also for our otoneurological expert system, One, which is based on a pattern recognition approach. The methods are able to differentiate most of the cases tested between the six diseases included, provided that a sufficiently large training set is available.