TY - JOUR AU - Li, W. AU - Song, F. AU - Wang, X. PY - 2019 DA - 2019// TI - Relationship between metabolic syndrome and its components and cardiovascular disease in middle-aged and elderly Chinese population: a national cross-sectional survey JO - BMJ Open VL - 9 ID - Li2019 ER - TY - JOUR AU - Low, S. AU - Khoo, K. AU - Wang, J. PY - 2019 DA - 2019// TI - Development of a metabolic syndrome severity score and its association with incident diabetes in an Asian population—results from a longitudinal cohort in Singapore JO - Endocrine VL - 65 UR - https://doi.org/10.1007/s12020-019-01970-5 DO - 10.1007/s12020-019-01970-5 ID - Low2019 ER - TY - JOUR AU - Chen, J. AU - Kong, X. AU - Jia, X. PY - 2017 DA - 2017// TI - Association between metabolic syndrome and chronic kidney disease in a Chinese urban population JO - Clin Chim Acta VL - 470 UR - https://doi.org/10.1016/j.cca.2017.05.012 DO - 10.1016/j.cca.2017.05.012 ID - Chen2017 ER - TY - JOUR AU - Alberti, K. G. AU - Zimmet, P. Z. PY - 1998 DA - 1998// TI - Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. Provisional report of a WHO consultation JO - Diabet Med VL - 15 UR - https://doi.org/3.0.CO;2-S DO - 3.0.CO;2-S ID - Alberti1998 ER - TY - JOUR AU - Kuhar, M. B. PY - 2001 DA - 2001// TI - Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) JO - Circulation VL - 106 ID - Kuhar2001 ER - TY - JOUR PY - 2004 DA - 2004// TI - Recommendations of the Chinese Medical Association diabetes branch on metabolic syndrome JO - Chin J Diabetes VL - 12 ID - ref6 ER - TY - JOUR AU - Alberti, K. G. AU - Zimmet, P. AU - Shaw, J. PY - 2006 DA - 2006// TI - Metabolic syndrome-a new world-wide definition.A consensus statement from the international diabetes federation JO - Diabetic Med VL - 23 UR - https://doi.org/10.1111/j.1464-5491.2006.01858.x DO - 10.1111/j.1464-5491.2006.01858.x ID - Alberti2006 ER - TY - JOUR AU - Alberti, K. AU - Eckel, R. H. AU - Grundy, S. M. PY - 2009 DA - 2009// TI - Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; national heart, lung, and blood institute; American heart association; world heart federation; international atherosclerosis society; and international association for the study of obesity JO - Circulation. VL - 120 UR - https://doi.org/10.1161/CIRCULATIONAHA.109.192644 DO - 10.1161/CIRCULATIONAHA.109.192644 ID - Alberti2009 ER - TY - JOUR AU - Al-Thani, M. H. AU - Al-Thani, A. A. M. AU - Cheema, S. PY - 2016 DA - 2016// TI - Prevalence and determinants of metabolic syndrome in Qatar: results from a National Health Survey JO - BMJ Open VL - 6 UR - https://doi.org/10.1136/bmjopen-2015-009514 DO - 10.1136/bmjopen-2015-009514 ID - Al-Thani2016 ER - TY - JOUR AU - Shin, D. AU - Kongpakpaisarn, K. AU - Bohra, C. PY - 2018 DA - 2018// TI - Trends in the prevalence of metabolic syndrome and its components in the United States 2007–2014 JO - Int J Cardiol VL - 259 UR - https://doi.org/10.1016/j.ijcard.2018.01.139 DO - 10.1016/j.ijcard.2018.01.139 ID - Shin2018 ER - TY - JOUR AU - Lee, S. E. AU - Han, K. AU - Kang, Y. M. PY - 2018 DA - 2018// TI - Trends in the prevalence of metabolic syndrome and its components in South Korea: findings from the Korean National Health Insurance Service database (2009–2013) JO - PLoS One VL - 13 ID - Lee2018 ER - TY - JOUR AU - Lu, J. AU - Wang, L. AU - Li, M. PY - 2017 DA - 2017// TI - Metabolic syndrome among adults in China: the 2010 China noncommunicable disease surveillance JO - J Clin Endocrinol Metab VL - 102 ID - Lu2017 ER - TY - BOOK AU - Liu, T. PY - 2017 DA - 2017// TI - Prevalence and risk factors of metabolic syndrome among residents in Jilin Province. MA dissertation PB - Jilin University CY - Jilin ID - Liu2017 ER - TY - JOUR AU - Li, R. AU - Li, W. AU - Lun, Z. PY - 2016 DA - 2016// TI - Prevalence of metabolic syndrome in mainland China: a meta-analysis of published studies JO - BMC Public Health VL - 16 UR - https://doi.org/10.1186/s12889-016-2870-y DO - 10.1186/s12889-016-2870-y ID - Li2016 ER - TY - JOUR AU - Li, Q. Z. AU - Rui, Z. PY - 2015 DA - 2015// TI - Research progress on evaluation methods of fit degree of disease risk prediction model JO - Chin Health Stat VL - 32 ID - Li2015 ER - TY - JOUR AU - Choe, E. K. AU - Rhee, H. AU - Lee, S. PY - 2018 DA - 2018// TI - Metabolic syndrome prediction using machine learning models with genetic and clinical information from a nonobese healthy population JO - Genom Inform VL - 16 UR - https://doi.org/10.5808/GI.2018.16.4.e31 DO - 10.5808/GI.2018.16.4.e31 ID - Choe2018 ER - TY - JOUR AU - Worachartcheewan, A. AU - Schaduangrat, N. AU - Prachayasittikul, V. PY - 2018 DA - 2018// TI - Data mining for the identification of metabolic syndrome status JO - EXCLI J VL - 17 ID - Worachartcheewan2018 ER - TY - JOUR AU - Mu, D. Y. AU - Hu, W. AU - Ma, Y. PY - 2019 DA - 2019// TI - Influencing factors and risk forecast model of metabolic syndrome among college faculties, Chengdu JO - Modern Prev Med VL - 46 ID - Mu2019 ER - TY - JOUR AU - Fatekurohman, M. AU - Nurmala, N. AU - Anggraeni, D. PY - 2018 DA - 2018// TI - Comparison of exact, efron and breslow parameter approach method on hazard ratio and stratified cox regression model JO - J Phys Conf Ser VL - 1008 ID - Fatekurohman2018 ER - TY - JOUR AU - Sohrabi, S. AU - Atashi, A. AU - Dadashi, A. PY - 2018 DA - 2018// TI - A comparative study of multilayer neural network and C4. 5 decision tree models for predicting the risk of breast Cancer JO - Archiv Breast Cancer VL - 5 ID - Sohrabi2018 ER - TY - JOUR AU - Tran, D. P. AU - Hoang, V. D. PY - 2019 DA - 2019// TI - Adaptive learning based on tracking and ReIdentifying objects using convolutional neural network JO - Neural Process Lett VL - 50 UR - https://doi.org/10.1007/s11063-019-10040-w DO - 10.1007/s11063-019-10040-w ID - Tran2019 ER - TY - JOUR AU - Gary, S. C. AU - Johannes, B. R. AU - Douglas, G. A. PY - 2015 DA - 2015// TI - Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement JO - Eur Urol VL - 67 UR - https://doi.org/10.1016/j.eururo.2014.11.025 DO - 10.1016/j.eururo.2014.11.025 ID - Gary2015 ER - TY - JOUR AU - Riley, R. D. AU - Snell, K. I. AU - Ensor, J. PY - 2019 DA - 2019// TI - Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes JO - Stat Med VL - 38 UR - https://doi.org/10.1002/sim.7992 DO - 10.1002/sim.7992 ID - Riley2019 ER - TY - JOUR AU - Szabo, D. E. F. AU - Goumidi, L. AU - Bertrais, S. PY - 2008 DA - 2008// TI - Prediction of the metabolic syndrome status based on dietary and genetic parameters, using random Forest JO - Genes Nutr VL - 3 UR - https://doi.org/10.1007/s12263-008-0097-y DO - 10.1007/s12263-008-0097-y ID - Szabo2008 ER - TY - JOUR AU - Lin, C. C. AU - Bai, Y. M. AU - Chen, J. Y. PY - 2010 DA - 2010// TI - Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models JO - J Clin Psychiatry VL - 71 UR - https://doi.org/10.4088/JCP.08m04628yel DO - 10.4088/JCP.08m04628yel ID - Lin2010 ER - TY - STD TI - Worachartcheewan A, Shoombuatong W, Pidetcha P, et al. Predicting metabolic syndrome using the random forest method. Sci World J. 2015. https://doi.org/10.1155/2015/581501. ID - ref26 ER - TY - JOUR AU - Karimi-Alavijeh, F. AU - Jalili, S. AU - Sadeghi, M. PY - 2016 DA - 2016// TI - Predicting metabolic syndrome using decision tree and support vector machine methods JO - ARYA Atherosclerosis VL - 12 ID - Karimi-Alavijeh2016 ER - TY - JOUR AU - Soltani, S. AU - Moslehi, N. AU - Hosseini-Esfahani, F. PY - 2018 DA - 2018// TI - The association between empirical dietary inflammatory pattern and metabolic phenotypes in overweight/obese adults JO - Int J Endocrinol Metab VL - 16 UR - https://doi.org/10.5812/ijem.60048 DO - 10.5812/ijem.60048 ID - Soltani2018 ER - TY - JOUR AU - Antonella, A. AU - Andrea, M. AU - Sarka, K. PY - 2018 DA - 2018// TI - Association of Dietary Patterns with metabolic syndrome: results from the Kardiovize Brno 2030 study JO - Nutrients VL - 10 UR - https://doi.org/10.3390/nu10070898 DO - 10.3390/nu10070898 ID - Antonella2018 ER - TY - JOUR AU - Rashidi, H. AU - Shahbazian, H. AU - Nokhostin, F. PY - 2018 DA - 2018// TI - The comparison of insulin and uric acid levels in adolescents with and without metabolic syndrome JO - Front Biol VL - 13 UR - https://doi.org/10.1007/s11515-018-1515-1 DO - 10.1007/s11515-018-1515-1 ID - Rashidi2018 ER - TY - JOUR AU - Khalili, M. AU - Shuhart, M. C. AU - Lombardero, M. PY - 2018 DA - 2018// TI - Relationship between metabolic syndrome, alanine aminotransferase levels, and liver disease severity in a multiethnic north American cohort with chronic hepatitis B JO - Diabetes Care VL - 41 UR - https://doi.org/10.2337/dc18-0040 DO - 10.2337/dc18-0040 ID - Khalili2018 ER - TY - JOUR AU - James, S. M. AU - Honn, K. A. AU - Gaddameedhi, S. PY - 2017 DA - 2017// TI - Shift work: disrupted circadian rhythms and sleep—implications for health and well-being JO - Curr Sleep Med Rep VL - 3 UR - https://doi.org/10.1007/s40675-017-0071-6 DO - 10.1007/s40675-017-0071-6 ID - James2017 ER - TY - JOUR AU - Vinogradova, I. AU - Anisimov, V. PY - 2013 DA - 2013// TI - Melatonin prevents the development of the metabolic syndrome in male rats exposed to different light/dark regimens JO - Biogerontology. VL - 14 UR - https://doi.org/10.1007/s10522-013-9437-4 DO - 10.1007/s10522-013-9437-4 ID - Vinogradova2013 ER - TY - JOUR AU - Schwartsburd, P. M. PY - 2017 DA - 2017// TI - Catabolic and anabolic faces of insulin resistance and their disorders: a new insight into circadian control of metabolic disorders leading to diabetes JO - Future Science OA VL - 3 UR - https://doi.org/10.4155/fsoa-2017-0015 DO - 10.4155/fsoa-2017-0015 ID - Schwartsburd2017 ER - TY - JOUR AU - Kar, D. AU - Gillies, C. AU - Nath, M. PY - 2019 DA - 2019// TI - Association of smoking and cardiometabolic parameters with albuminuria in people with type 2 diabetes mellitus: a systematic review and meta-analysis JO - Acta Diabetol VL - 56 UR - https://doi.org/10.1007/s00592-019-01293-x DO - 10.1007/s00592-019-01293-x ID - Kar2019 ER - TY - JOUR AU - Peter, C. A. AU - Ewout, W. S. PY - 2019 DA - 2019// TI - The integrated calibration index (ICI) and related metrics for quantifying the calibration of logistic regression models JO - Stat Med VL - 38 UR - https://doi.org/10.1002/sim.8281 DO - 10.1002/sim.8281 ID - Peter2019 ER - TY - JOUR AU - Al-Quraishi, T. AU - Abawajy, J. H. AU - Chowdhury, M. U. PY - 2018 DA - 2018// TI - Breast Cancer recurrence prediction using random Forest model JO - Recent Adv Soft Comput Data Mining VL - 700 UR - https://doi.org/10.1007/978-3-319-72550-5_31 DO - 10.1007/978-3-319-72550-5_31 ID - Al-Quraishi2018 ER - TY - JOUR AU - Dagliati, A. AU - Marini, S. AU - Sacchi, L. PY - 2018 DA - 2018// TI - Machine learning methods to predict diabetes complications JO - J Diabetes Sci Technol VL - 12 UR - https://doi.org/10.1177/1932296817706375 DO - 10.1177/1932296817706375 ID - Dagliati2018 ER - TY - JOUR AU - Wu, J. H. AU - Li, J. AU - Wang, J. PY - 2020 DA - 2020// TI - Risk prediction of type 2 diabetes in steel workers based on convolutional neural network JO - Neural Comput & Applic VL - 32 UR - https://doi.org/10.1007/s00521-019-04489-y DO - 10.1007/s00521-019-04489-y ID - Wu2020 ER - TY - JOUR AU - Ševo, I. AU - Avramović, A. PY - 2016 DA - 2016// TI - Convolutional neural network based automatic object detection on aerial images JO - IEEE Geosci Remote Sens Lett VL - 13 UR - https://doi.org/10.1109/LGRS.2016.2542358 DO - 10.1109/LGRS.2016.2542358 ID - Ševo2016 ER - TY - BOOK AU - Mu-han, D. PY - 2018 DA - 2018// TI - Prediction of epileptic seizures based on convolution neural network. MA dissertation PB - Shandong Normal University CY - Shandong ID - Mu-han2018 ER - TY - JOUR AU - Zhang, M. AU - Wang, L. M. AU - Chen, Z. H. PY - 2018 DA - 2018// TI - Multilevel logistic regression analysis on hypercholesterolemia related risk factors among adults in China JO - Chin J Prev Med VL - 52 ID - Zhang2018 ER -