{"title":"模式识别软件用于新生儿心血管风险评估","authors":"R. Hermida, J. R. Fernández, D. Ayala, F. Aguado","doi":"10.1109/IEMBS.1992.5761567","DOIUrl":null,"url":null,"abstract":"Parametric characteristics obtained by least-squares fitting and descriptive statistics of within-a-day variability in blood pressure and heart rate for 150 neonates are here used for classification according to a cardiovascular risk score by the use of an all-subsets variable selection technique for discriminant analysis, specifically designed for biomedical applications. Results provide a set of classification criteria for further use in neonatal risk assessment.1","PeriodicalId":6457,"journal":{"name":"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":"127 1","pages":"2518-2519"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pattern discrimination software for neonatal cardiovascular risk estimation\",\"authors\":\"R. Hermida, J. R. Fernández, D. Ayala, F. Aguado\",\"doi\":\"10.1109/IEMBS.1992.5761567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Parametric characteristics obtained by least-squares fitting and descriptive statistics of within-a-day variability in blood pressure and heart rate for 150 neonates are here used for classification according to a cardiovascular risk score by the use of an all-subsets variable selection technique for discriminant analysis, specifically designed for biomedical applications. Results provide a set of classification criteria for further use in neonatal risk assessment.1\",\"PeriodicalId\":6457,\"journal\":{\"name\":\"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"volume\":\"127 1\",\"pages\":\"2518-2519\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMBS.1992.5761567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1992.5761567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern discrimination software for neonatal cardiovascular risk estimation
Parametric characteristics obtained by least-squares fitting and descriptive statistics of within-a-day variability in blood pressure and heart rate for 150 neonates are here used for classification according to a cardiovascular risk score by the use of an all-subsets variable selection technique for discriminant analysis, specifically designed for biomedical applications. Results provide a set of classification criteria for further use in neonatal risk assessment.1
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
