A prediction model of cognitive impairment risk in elderly illiterate Chinese women
暂无分享,去创建一个
Yinyin Wu | Zhaojing Chen | Jun Yang | Qin Song | J. Du
[1] Shanhui Liu,et al. Diagnostic models and predictive drugs associated with cuproptosis hub genes in Alzheimer's disease , 2023, Frontiers in Neurology.
[2] Mi Jung Lee,et al. Developing a Machine Learning Prediction Model for Cognitive Dysfunction of Community-Dwelling Older Adults , 2022, Archives of Physical Medicine and Rehabilitation.
[3] L. Xiao,et al. Derivation and Validation of the Cognitive Impairment Prediction Model in Older Adults: A National Cohort Study , 2022, Frontiers in Aging Neuroscience.
[4] R. Mudar,et al. An Integrative Framework to Guide Social Engagement Interventions and Technology Design for Persons With Mild Cognitive Impairment , 2022, Frontiers in Public Health.
[5] Yi Zeng,et al. Chinese Longitudinal Healthy Longevity Survey (CLHLS) , 2021, Encyclopedia of Gerontology and Population Aging.
[6] H. Kang,et al. Trend Analysis of Average Frequency Using Toothbrushing per Day in South Korea: An Observational Study of the 2010 to 2018 KNHANES Data , 2021, International journal of environmental research and public health.
[7] Z. Chen,et al. [Random survival forest: applying machine learning algorithm in survival analysis of biomedical data]. , 2021, Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine].
[8] P. Austin,et al. Machine learning vs. conventional statistical models for predicting heart failure readmission and mortality , 2020, ESC heart failure.
[9] I. Olsen,et al. Low levels of salivary lactoferrin may affect oral dysbiosis and contribute to Alzheimer's disease: A hypothesis. , 2020, Medical hypotheses.
[10] M. Matveeva,et al. A Prognostic Model of the Development of Cognitive Impairments in Patients with Type 1 Diabetes Mellitus , 2020, Neuroscience and Behavioral Physiology.
[11] Li Jin,et al. Lifestyle, multi‐omics features, and preclinical dementia among Chinese: The Taizhou Imaging Study , 2020, Alzheimer's & dementia : the journal of the Alzheimer's Association.
[12] C. Mao,et al. Development and Validation of a Nomogram for Predicting the 6-Year Risk of Cognitive Impairment Among Chinese Older Adults. , 2020, Journal of the American Medical Directors Association.
[13] L. Tan,et al. Association of body mass index with risk of cognitive impairment and dementia: A systematic review and meta-analysis of prospective studies , 2020, Neuroscience & Biobehavioral Reviews.
[14] Xianbo Wu,et al. Age, period and cohort effects in activities of daily living, physical and cognitive functioning impairment among the oldest-old in China. , 2019, The journals of gerontology. Series A, Biological sciences and medical sciences.
[15] J. Tein,et al. The need to belong: A parallel process latent growth curve model of late life negative affect and cognitive function. , 2020, Archives of gerontology and geriatrics.
[16] Chen Bai,et al. Cognitive function and mental health of elderly people in China: findings from 2018 CLHLS survey , 2020 .
[17] Tao Zhang,et al. Body mass index, waist-to-hip ratio and cognitive function among Chinese elderly: a cross-sectional study , 2018, BMJ Open.
[18] C-C Lin,et al. Risk score prediction model for dementia in patients with type 2 diabetes , 2018, European journal of neurology.
[19] Weijun Peng,et al. A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules , 2018, European Radiology.
[20] M. Egger,et al. Body mass index in midlife and dementia: Systematic review and meta-regression analysis of 589,649 men and women followed in longitudinal studies , 2017, Alzheimer's & dementia.
[21] J. Schott,et al. Clinical variables and biomarkers in prediction of cognitive impairment in patients with newly diagnosed Parkinson's disease: a cohort study , 2017, The Lancet Neurology.
[22] Zijing Wu,et al. Resilience and Associated Factors among Mainland Chinese Women Newly Diagnosed with Breast Cancer , 2016, PloS one.
[23] Hae-Young Kim,et al. Gender-Specific Incidence and Predictors of Cognitive Impairment among Older Koreans: Findings from a 6-Year Prospective Cohort Study , 2016, Psychiatry investigation.
[24] Z. Hyde,et al. Incidence and predictors of cognitive impairment and dementia in Aboriginal Australians: A follow-up study of 5 years , 2016, Alzheimer's & Dementia.
[25] C. Jack,et al. Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging , 2015, Neurology.
[26] M. Šapurić,et al. Assessment of Knowledge and Attitudes to Preserve Oral Health among Older People Aged 60+ in FYROM , 2015 .
[27] M. Eriksdotter,et al. Body mass index in dementia , 2014, European Journal of Clinical Nutrition.
[28] Alzheimer's Disease Neuroimaging Initiative,et al. A point-based tool to predict conversion from mild cognitive impairment to probable Alzheimer's disease , 2014, Alzheimer's & Dementia.
[29] Hemant Ishwaran,et al. Random survival forests for competing risks. , 2014, Biostatistics.
[30] Yi Zeng,et al. Direct and indirect effects of childhood conditions on survival and health among male and female elderly in China. , 2014, Social science & medicine.
[31] S. Rubin,et al. Older adults with limited literacy are at increased risk for likely dementia. , 2014, The journals of gerontology. Series A, Biological sciences and medical sciences.
[32] B. Dong,et al. The measurement of disability in the elderly: a systematic review of self-reported questionnaires. , 2014, Journal of the American Medical Directors Association.
[33] Y. Wang,et al. Cognitive impairment using education‐based cutoff points for CMMSE scores in elderly Chinese people of agricultural and rural Shanghai China , 2011, Acta neurologica Scandinavica.
[34] Ó. Ribeiro,et al. Cognitive impairment in old people living in the community. , 2010, Archives of gerontology and geriatrics.
[35] H. Vankova. Mini Mental State , 2010 .
[36] C. Navarro,et al. Prevalence of dementia and cognitive impairment in Southeastern Spain: the Ariadna study , 2009, Acta neurologica Scandinavica.
[37] Elizabeth J. Malloy,et al. Comparing measures of model selection for penalized splines in Cox models , 2009, Comput. Stat. Data Anal..
[38] Hemant Ishwaran,et al. Random Survival Forests , 2008, Wiley StatsRef: Statistics Reference Online.
[39] P. Pezzotti,et al. The accuracy of the MMSE in detecting cognitive impairment when administered by general practitioners : A prospective observational study , 2015 .
[40] Suzanne G. Leveille,et al. Cognitive Function, Habitual Gait Speed, and Late-Life Disability in the National Health and Nutrition Examination Survey (NHANES) 1999–2002 , 2006, Gerontology.
[41] B. Winblad,et al. [Risk factors for dementia and Alzheimer' s disease-findings from a community-based cohort study in Stockholm, Sweden]. , 2005, Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi.
[42] P. Royston,et al. Flexible parametric proportional‐hazards and proportional‐odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects , 2002, Statistics in medicine.
[43] J. Morris,et al. Current concepts in mild cognitive impairment. , 2001, Archives of neurology.
[44] N H Ng'andu,et al. An empirical comparison of statistical tests for assessing the proportional hazards assumption of Cox's model. , 1997, Statistics in medicine.
[45] F. Harrell,et al. Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors , 2005 .
[46] K R Hess,et al. Graphical methods for assessing violations of the proportional hazards assumption in Cox regression. , 1995, Statistics in medicine.
[47] S. Folstein,et al. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.
[48] M. Inzitari,et al. Daily Function as Predictor of Dementia in Cognitive Impairment, No Dementia (CIND) and Mild Cognitive Impairment (MCI): An 8-Year Follow-Up in the ILSA Study. , 2016, Journal of Alzheimer's disease : JAD.
[49] Haewon Byeon,et al. A Prediction Model for Mild Cognitive Impairment Using Random Forests , 2015 .
[50] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[51] L. Kesavalu,et al. Determining the presence of periodontopathic virulence factors in short-term postmortem Alzheimer's disease brain tissue. , 2013, Journal of Alzheimer's disease : JAD.
[52] M. Haan,et al. Body adiposity in late life and risk of dementia or cognitive impairment in a longitudinal community-based study. , 2009, The journals of gerontology. Series A, Biological sciences and medical sciences.