V. Mrázová, J. Mocák, E. Varmusová, Denisa Kavková
{"title":"基于肿瘤标志物数据多维分析的肺恶性肿瘤计算机辅助诊断","authors":"V. Mrázová, J. Mocák, E. Varmusová, Denisa Kavková","doi":"10.36547/nbc.1309","DOIUrl":null,"url":null,"abstract":"The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.","PeriodicalId":19210,"journal":{"name":"Nova Biotechnologica et Chimica","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data\",\"authors\":\"V. Mrázová, J. Mocák, E. Varmusová, Denisa Kavková\",\"doi\":\"10.36547/nbc.1309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.\",\"PeriodicalId\":19210,\"journal\":{\"name\":\"Nova Biotechnologica et Chimica\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nova Biotechnologica et Chimica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36547/nbc.1309\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nova Biotechnologica et Chimica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36547/nbc.1309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data
The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.