Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes.
Sign Up to like & getrecommendations! Published in 2020 at "JAMA network open"
DOI: 10.1001/jamanetworkopen.2019.18962
Abstract: Importance Accurate risk stratification of patients with heart failure (HF) is critical to deploy targeted interventions aimed at improving patients' quality of life and outcomes. Objectives To compare machine learning approaches with traditional logistic regression… read more here.
Keywords: home; logistic regression; machine learning; regression ... See more keywords
Logistic regression models of cytokines in differentiating vitreoretinal lymphoma from uveitis
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Clinical Laboratory Analysis"
DOI: 10.1002/jcla.24689
Abstract: Vitreoretinal lymphoma (VRL) can commonly masquerade as chronic idiopathic uveitis due to its nonspecific clinical presentation. Thus, its early diagnosis is difficult. In this study, new logistic regression models were used to classify VRL and… read more here.
Keywords: uveitis; logistic regression; lymphoma; vitreoretinal lymphoma ... See more keywords
Machine learning versus multivariate logistic regression for predicting severe COVID‐19 in hospitalized children with Omicron variant infection
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DOI: 10.1002/jmv.29447
Abstract: With the emergence of the Omicron variant, the number of pediatric Coronavirus Disease 2019 (COVID‐19) cases requiring hospitalization and developing severe or critical illness has significantly increased. Machine learning and multivariate logistic regression analysis were… read more here.
Keywords: severe covid; logistic regression; machine learning; multivariate logistic ... See more keywords
Ultrasound Radiomics‐Based Logistic Regression Model to Differentiate Between Benign and Malignant Breast Nodules
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Ultrasound in Medicine"
DOI: 10.1002/jum.16078
Abstract: To explore the potential value of ultrasound radiomics in differentiating between benign and malignant breast nodules by extracting the radiomic features of two‐dimensional (2D) grayscale ultrasound images and establishing a logistic regression model. read more here.
Keywords: malignant breast; logistic regression; breast nodules; ultrasound radiomics ... See more keywords
Comparing external and internal validation methods in correcting outcome misclassification bias in logistic regression: A simulation study and application to the case of postsurgical venous thromboembolism following total hip and knee arthroplasty
Sign Up to like & getrecommendations! Published in 2019 at "Pharmacoepidemiology and Drug Safety"
DOI: 10.1002/pds.4693
Abstract: We assessed the validity of postsurgery venous thromboembolism (VTE) diagnoses identified from administrative databases and compared Bayesian and multiple imputation (MI) approaches in correcting for outcome misclassification in logistic regression models. read more here.
Keywords: venous thromboembolism; outcome misclassification; logistic regression; correcting outcome ... See more keywords
Equivalency Between the Generalized Bivariate Bernoulli Model Dependency Test and a Logistic Regression Model With Interaction Effects
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DOI: 10.1002/sim.70260
Abstract: Binary endpoints measured at two timepoints—such as pre‐ and post‐treatment—are common in biomedical and healthcare research. The Generalized Bivariate Bernoulli Model (GBBM) provides a specialized framework for analyzing such bivariate binary data, allowing for formal… read more here.
Keywords: bernoulli model; bivariate bernoulli; logistic regression; model ... See more keywords
Doubly robust conditional logistic regression.
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DOI: 10.1002/sim.8332
Abstract: Epidemiologic research often aims to estimate the association between a binary exposure and a binary outcome, while adjusting for a set of covariates (eg, confounders). When data are clustered, as in, for instance, matched case-control… read more here.
Keywords: conditional logistic; logistic regression; robust conditional; odds ratio ... See more keywords
“Improving the performance of Bayesian logistic regression model with overdose control in oncology dose‐finding studies” by Hongtao Zhang, Alan Chiang, and Jixian Wang
Sign Up to like & getrecommendations! Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9494
Abstract: In their paper, Zhang et al 1 propose further extensions of the Bayesian Logistic Regression Model (BLRM) with overdose control for dose-escalation studies of a novel drug. These extensions aim to reduce the risk of… read more here.
Keywords: oncology; logistic regression; zhang; overdose control ... See more keywords
Commentary on “Improving the performance of Bayesian logistic regression model with overdose control in oncology dose‐finding studies”
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DOI: 10.1002/sim.9496
Abstract: The Bayesian logistic regression model (BLRM) design is a variation of the continuous reassessment method (CRM). Due to the use of an excessively tight escalation with overdose control (EWOC) rule, BLRM has high tendency to… read more here.
Keywords: oncology; logistic regression; overdose control; bayesian logistic ... See more keywords
Semi-supervised inference for nonparametric logistic regression.
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DOI: 10.1002/sim.9737
Abstract: We consider the problem of estimating the nonparametric function in nonparametric logistic regression under semi-supervised framework, where a relatively small size labeled data set collected by case-control sampling and a relatively large size of unlabeled… read more here.
Keywords: semi supervised; nonparametric logistic; function; logistic regression ... See more keywords
Saddlepoint approximations to score test statistics in logistic regression for analyzing genome-wide association studies.
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DOI: 10.1002/sim.9746
Abstract: We investigate saddlepoint approximations of tail probabilities of the score test statistic in logistic regression for genome-wide association studies. The inaccuracy in the normal approximation of the score test statistic increases with increasing imbalance in… read more here.
Keywords: saddlepoint approximations; genome wide; logistic regression; score test ... See more keywords