{"title":"医学中进化数据的呈现与自动处理。临床胰腺病理的应用[j]。","authors":"M Rodriguez, R C Cros, J Cornée","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper we propose a method allowing the representation of time-dependent changes in symptomatology. In algorithm, which automatically generates the sequence of stable states in patient's symptomatology evolution, describes slow, as well as fast, variations of diseases. This sequential representation of data can then be analysed by classical statistical procedures in a population of patients suffering from pancreatic diseases, to estimate the rate of global modification of clinical symptomatology in time.</p>","PeriodicalId":10544,"journal":{"name":"Comptes rendus hebdomadaires des seances de l'Academie des sciences. Serie D: Sciences naturelles","volume":"287 12","pages":"1165-8"},"PeriodicalIF":0.0000,"publicationDate":"1978-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Presentation and automatic treatment of evolutive data in medicine. Application to clinical pancreatic pathology].\",\"authors\":\"M Rodriguez, R C Cros, J Cornée\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper we propose a method allowing the representation of time-dependent changes in symptomatology. In algorithm, which automatically generates the sequence of stable states in patient's symptomatology evolution, describes slow, as well as fast, variations of diseases. This sequential representation of data can then be analysed by classical statistical procedures in a population of patients suffering from pancreatic diseases, to estimate the rate of global modification of clinical symptomatology in time.</p>\",\"PeriodicalId\":10544,\"journal\":{\"name\":\"Comptes rendus hebdomadaires des seances de l'Academie des sciences. Serie D: Sciences naturelles\",\"volume\":\"287 12\",\"pages\":\"1165-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1978-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comptes rendus hebdomadaires des seances de l'Academie des sciences. Serie D: Sciences naturelles\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comptes rendus hebdomadaires des seances de l'Academie des sciences. Serie D: Sciences naturelles","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Presentation and automatic treatment of evolutive data in medicine. Application to clinical pancreatic pathology].
In this paper we propose a method allowing the representation of time-dependent changes in symptomatology. In algorithm, which automatically generates the sequence of stable states in patient's symptomatology evolution, describes slow, as well as fast, variations of diseases. This sequential representation of data can then be analysed by classical statistical procedures in a population of patients suffering from pancreatic diseases, to estimate the rate of global modification of clinical symptomatology in time.