{"title":"PREDICTORS OF INFLAMMATION IN FIREFIGHTERS BASED ON MACHINE LEARNING MODELS","authors":"","doi":"10.1016/j.annepidem.2024.07.021","DOIUrl":"10.1016/j.annepidem.2024.07.021","url":null,"abstract":"","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":"142232980","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}
{"title":"SEXUAL BEHAVIORS ASSOCIATED WITH HIV TESTING AMONG U.S. HIGH SCHOOLERS","authors":"","doi":"10.1016/j.annepidem.2024.07.017","DOIUrl":"10.1016/j.annepidem.2024.07.017","url":null,"abstract":"","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":"142232983","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}
{"title":"A Reference framework for integrating advanced algorithms into decision support in a public health emergency","authors":"","doi":"10.1016/j.annepidem.2024.07.092","DOIUrl":"10.1016/j.annepidem.2024.07.092","url":null,"abstract":"","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":"142233024","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}
{"title":"COMPARISON OF SUPPORT VECTOR REGRESSION AND BOX-COX POWER EXPONENTIAL-GENERALIZED ADDITIVE MODEL FOR LOCATION, SCALE, AND SHAPE (BCPE-GAMLSS) IN PREDICTION OF BODY MASS INDEX","authors":"","doi":"10.1016/j.annepidem.2024.07.067","DOIUrl":"10.1016/j.annepidem.2024.07.067","url":null,"abstract":"","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":"142231964","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}
{"title":"PREDICTING RISK OF EMPLOYEE INJURY IN A PEDIATRIC HOSPITAL","authors":"","doi":"10.1016/j.annepidem.2024.06.014","DOIUrl":"10.1016/j.annepidem.2024.06.014","url":null,"abstract":"<div><h3><strong>PURPOSE</strong></h3><p>Healthcare has one of the highest rates of non-fatal occupational injury as compared to other industries. Yet, evaluation of risk determinants and prediction algorithms in hospital settings remains limited.</p></div><div><h3><strong>METHODS</strong></h3><p>This study examines risk factors for employee injuries in a large pediatric hospital and evaluates prediction algorithms using hospital surveillance data, incident reports, and work unit measures such as patient density and employee workload. We employed multiple statistical models and machine learning tools, including logistic regression (LR), random forest (RF), penalized logistic regression (PLR), Naïve Bayes, neural network (NN), XGBoost (XG), and mixed-effects logistic regression (GLMER) to predict employee injury risk for specific time periods. We used cross-validation and receiver-operator characteristic (ROC) curve analyses to assess model performance.</p></div><div><h3><strong>RESULTS</strong></h3><p>GLMER, LR, and PLR were superior to other models, with higher AUC values (∼0.76), indicating good discrimination ability, though accuracy and specificity varied across models. RF showed high accuracy and specificity and comparable AUC with the top performing models. Further analyses using GLMER revealed variability in employee injury risk across months, days, and hospital units, identifying peaks on Tuesdays and Saturdays and in April and July, with lows in March and June.</p></div><div><h3><strong>CONCLUSION</strong></h3><p>Our findings highlight the significance of monitoring specific risk factors within pediatric hospital settings and pairing them with appropriate predictive algorithms to effectively predict and mitigate employee injuries. These insights indicate that continuous monitoring may help enhance employee safety. Future work should evaluate additional predictors that may be obtained from individual hospital units, which may inform targeted prevention strategies.</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":"142232771","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}
{"title":"Examining word patterns and trends in self-harm emergency department narratives","authors":"","doi":"10.1016/j.annepidem.2024.07.062","DOIUrl":"10.1016/j.annepidem.2024.07.062","url":null,"abstract":"","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":"142232348","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}
{"title":"HIV AND STI TESTING AMONG SEXUALLY ACTIVE ADOLESCENTS: YRBS, 2021","authors":"","doi":"10.1016/j.annepidem.2024.07.057","DOIUrl":"10.1016/j.annepidem.2024.07.057","url":null,"abstract":"","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":"142232204","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}
{"title":"Words matter: Ensuring the inclusion of neurodivergent populations in digital surveillance of depression and suicidal ideation","authors":"","doi":"10.1016/j.annepidem.2024.07.068","DOIUrl":"10.1016/j.annepidem.2024.07.068","url":null,"abstract":"","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":"142232781","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}
{"title":"Leveraging AI and NLP to Uncover real-world experiences with semaglutide for weight loss","authors":"","doi":"10.1016/j.annepidem.2024.07.054","DOIUrl":"10.1016/j.annepidem.2024.07.054","url":null,"abstract":"","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":"142232528","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}
{"title":"Prediction of Depression in HCV Population Based on Machine Learning","authors":"","doi":"10.1016/j.annepidem.2024.07.082","DOIUrl":"10.1016/j.annepidem.2024.07.082","url":null,"abstract":"","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":"142232777","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}