Search Results - computer prevalence diagnosis｜((em algorithms) OR (((ascent algorithms) OR (mining algorithms)))) :: K.UTB vyhledávací portál

Comparing Three Data Mining Algorithms for Identifying the Associated Risk Factors of Type 2 Diabetes

by Esmaeily, Habibollah, Tayefi, Maryam, Ghayour-Mobarhan, Majid, Amirabadizadeh, Alireza
Published in Iranian biomedical journal (01.09.2018)

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Computational methods to simultaneously compare the predictive values of two diagnostic tests with missing data: EM-SEM algorithms and multiple imputation

by Roldán-Nofuentes, J. A.
Published in Journal of statistical computation and simulation (02.11.2021)

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Probit Latent Class Model with General Correlation Structures for Evaluating Accuracy of Diagnostic Tests

by Xu, Huiping, Craig, Bruce A.
Published in Biometrics (01.12.2009)

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Estimating the prevalence of osteoporosis using ranked-based methodologies and Manitoba's population-based BMD registry

by Omidvar, Sedigheh, Jafari Jozani, Mohammad, Nematollahi, Nader, Leslie, Wiliam D.
Published in Journal of applied statistics (17.08.2024)

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Penalized regression for interval-censored times of disease progression: Selection of HLA markers in psoriatic arthritis

by Wu, Ying, Cook, Richard J.
Published in Biometrics (01.09.2015)

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“TAGS”, a program for the evaluation of test accuracy in the absence of a gold standard

by Pouillot, Régis, Gerbier, Guillaume, Gardner, Ian A.
Published in Preventive veterinary medicine (14.02.2002)

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Efficient Algorithms for Mining Healthcare Data

by Hu, Yan
Year of Publication 01.01.2019

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EM and SEM algorithms to compare the weighted kappa coefficients of two diagnostic tests in the presence of partial verification and discrete covariates

by Roldán-Nofuentes, J. A., Sidaty-Regad, S. B.
Published in Journal of statistical computation and simulation (11.12.2020)

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A comprehensive review of machine learning techniques on diabetes detection

by Sharma, Toshita, Shah, Manan
Published in Visual computing for industry, biomedicine and art (03.12.2021)

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A time-varying measurement error model for age of onset of a psychiatric diagnosis: applied to first depressive episode diagnosed by the Composite International Diagnostic Interview (CIDI)

by Klungsøyr, Ole, Sexton, Joe, Sandanger, Inger, Nygård, Jan F.
Published in Journal of applied statistics (01.04.2013)

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Comparison of the Average Kappa Coefficients of Two Binary Diagnostic Tests with Missing Data

by Roldán-Nofuentes, José Antonio, Regad, Saad Bouh
Published in Mathematics (Basel) (01.11.2021)

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Data analytics identify glycated haemoglobin co-markers for type 2 diabetes mellitus diagnosis

by Jelinek, Herbert F., Stranieri, Andrew, Yatsko, Andrew, Venkatraman, Sitalakshmi
Published in Computers in biology and medicine (01.08.2016)

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Automatic detection of referral patients due to retinal pathologies through data mining

by Quellec, Gwenolé, Lamard, Mathieu, Erginay, Ali, Chabouis, Agnès, Massin, Pascale, Cochener, Béatrice, Cazuguel, Guy
Published in Medical image analysis (01.04.2016)

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Mapping Cancer Risk in Southwestern Ontario with Changing Census Boundaries

by Nguyen, P., Brown, P. E., Stafford, J.
Published in Biometrics (01.12.2012)

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Estimating Diagnostic Accuracy of Raters Without a Gold Standard by Exploiting a Group of Experts

by Zhang, Bo, Chen, Zhen, Albert, Paul S.
Published in Biometrics (01.12.2012)

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An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence

by Allen, Ben
Published in PloS one (05.10.2023)

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Mining Google Trends data for nowcasting and forecasting colorectal cancer (CRC) prevalence

by Tudor, Cristiana, Sova, Robert Aurelian
Published in PeerJ. Computer science (04.10.2023)

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Evaluation of incomplete multiple diagnostic tests, with an application in the colon cancer family registry study

by Zhang, Yi, Chu, Haitao, Zeng, Donglin
Published in Journal of applied statistics (04.03.2014)

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Characterizing clinical pediatric obesity subtypes using electronic health record data

by Campbell, Elizabeth A., Maltenfort, Mitchell G., Shults, Justine, Forrest, Christopher B., Masino, Aaron J.
Published in PLOS digital health (01.08.2022)

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Social media mining for birth defects research: A rule-based, bootstrapping approach to collecting data for rare health-related events on Twitter

by Klein, Ari Z., Sarker, Abeed, Cai, Haitao, Weissenbacher, Davy, Gonzalez-Hernandez, Graciela
Published in Journal of biomedical informatics (01.11.2018)

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