{"title":"流式细胞术数据多变量分析的混合系统方法","authors":"L. Fu, M. Yang, R. Braylan, N. Benson","doi":"10.1109/CBMS.1992.244933","DOIUrl":null,"url":null,"abstract":"In dealing with massive flow cytometric data, an adaptive data analysis scheme has been developed. The problem solving structure is configured as a connectionist network. Information is encoded in the form of connection weights. The structure evolves as more data are seen by adjusting its weights, governed by a learning equation. The knowledge embedded in the network can be further decoded in symbolic form. The results are reported from the domain of measuring the antigenic properties of blood samples. The technique has been validated statistically with respect to its self-consistency and determinacy.<<ETX>>","PeriodicalId":197891,"journal":{"name":"[1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A hybrid system approach to multivariate analysis of flow cytometry data\",\"authors\":\"L. Fu, M. Yang, R. Braylan, N. Benson\",\"doi\":\"10.1109/CBMS.1992.244933\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In dealing with massive flow cytometric data, an adaptive data analysis scheme has been developed. The problem solving structure is configured as a connectionist network. Information is encoded in the form of connection weights. The structure evolves as more data are seen by adjusting its weights, governed by a learning equation. The knowledge embedded in the network can be further decoded in symbolic form. The results are reported from the domain of measuring the antigenic properties of blood samples. The technique has been validated statistically with respect to its self-consistency and determinacy.<<ETX>>\",\"PeriodicalId\":197891,\"journal\":{\"name\":\"[1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.1992.244933\",\"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] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.1992.244933","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A hybrid system approach to multivariate analysis of flow cytometry data
In dealing with massive flow cytometric data, an adaptive data analysis scheme has been developed. The problem solving structure is configured as a connectionist network. Information is encoded in the form of connection weights. The structure evolves as more data are seen by adjusting its weights, governed by a learning equation. The knowledge embedded in the network can be further decoded in symbolic form. The results are reported from the domain of measuring the antigenic properties of blood samples. The technique has been validated statistically with respect to its self-consistency and determinacy.<>
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