Annals of Epidemiology最新文献_第5页

Integrating a machine learning algorithm to forecast daily asthma hospitalizations 整合机器学习算法，预测每天的哮喘住院人数

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.006

S.P. Colegate , M. Seid , D. Hartley , J. Bruce , A.F. Beck , C. Brokamp

引用次数: 0

Trends in hospital births diagnosed with Neonatal Abstinence Syndrome (NAS) during the COVID-19 pandemic in the US 在美国 COVID-19 大流行期间，经医院诊断患有新生儿禁食综合症 (NAS) 的新生儿趋势

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.061

A. Crawford, P. Singh

引用次数: 0

The long-term Particulate Matter2.5 exposure and prevalent COPD 长期暴露于颗粒物 2.5 与慢性阻塞性肺病的发病率

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.028

Matthew R. Bonner PhD, MPH, T. Milillo, M. Wang, L. Mu, L. Tumiel Berhalter, J.R. Olson

引用次数: 0

Prediction of longitudinal risk for chronic obstructive pulmonary disease 慢性阻塞性肺病纵向风险预测

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.06.013

Maiwulamujiang Maimaitiyiming PhD , Rongrong Yang PhD , Xiuying Qi PhD

引用次数: 0

Trends & racial disparities in stroke mortality in the US 美国中风死亡率的趋势和种族差异

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.090

Edwin Akomaning, Samuel Prince Osei, Akshaya Bhagavathula

引用次数: 0

Perceptions towards Chatbots addressing unmet social needs among Low-Income Households 低收入家庭对聊天机器人解决未满足的社会需求的看法

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.035

Emre Sezgin PhD, Daniel I. Jackson BSc, Millie Dolce PhD, Alex Kemper MD

引用次数: 0

The association between everyday discrimination and perinatal depression in a birth cohort in Cincinnati, Ohio 俄亥俄州辛辛那提市一个出生队列中的日常歧视与围产期抑郁之间的关系

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.075

Katherine Bowers, Kaela Boulay, Shelby Alderman, Alonzo Folger

引用次数: 0

Social determinants of health to predict type 2 diabetes 预测 2 型糖尿病的健康社会决定因素

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.04.014

{"title":"Social determinants of health to predict type 2 diabetes","authors":"","doi":"10.1016/j.annepidem.2024.04.014","DOIUrl":"10.1016/j.annepidem.2024.04.014","url":null,"abstract":"<div><h3>Purpose</h3><p>Though, type 2 diabetes (T2DM) is largely genetically heritable, several environmental factors could contribute to the occurrence of T2DM. The current study employed machine learning (ML) algorithms to predict the risk of T2DM using the social determinants of health reported in the All of Us Research Program Data.</p></div><div><h3>Methods</h3><p>Data were sourced from the All of Us Research Program. All patients with a complete record of the social determinants of health survey were included in the analysis. The participants were categorized based on history of diabetes (case = 1) and without history of diabetes (case = 0). The major ML models tested were gradient boost model, RandomForest model, and support vector machines. The model performance measures include accuracy, precision, and recall. Feature importance was evaluated based on the mean decrease in accuracy score, an output from the best model.</p></div><div><h3>Results</h3><p>Overall, the social determinants of health were able to improve the performance of the ML models to predict the risk of T2DM. The accuracy of the ML models was in the range of 88%–92%. The sensitivity of all the models were more-than 90%. Also, important features out of the social determinants, were reported as predictors of T2DM.</p></div><div><h3>Conclusion</h3><p>The social determinants of health reported in the All of Us dataset were able to predict the risk of diabetes using machine learning algorithms. These factors could be used to screen patients with a risk of T2DM.</p></div>","PeriodicalId":50767,"journal":{"name":"Annals of Epidemiology","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141280851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The incidence and mortality of cervical cancer and its relation with the level of countries socioeconomic development 宫颈癌的发病率和死亡率及其与各国社会经济发展水平的关系

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.081

Marzieh Eslahi , Samaneh Torkian , Narges Khanjani

引用次数: 0

Caste disparities in medical sterilization regret among women in India 印度妇女医疗绝育遗憾中的种姓差异

IF 3.3 3区医学

Annals of Epidemiology Pub Date : 2024-09-01 DOI: 10.1016/j.annepidem.2024.07.066

Sage Smith, Parvati Singh

引用次数: 0