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Binary classification with fuzzy logistic regression under class imbalance and complete separation in clinical studies
BackgroundIn binary classification for clinical studies, an imbalanced distribution of cases to classes and an extreme association level between the...
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Logistic regression and other statistical tools in diagnostic biomarker studies
A biomarker is a measured indicator of a variety of processes, and is often used as a clinical tool for the diagnosis of diseases. While the...
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Adjusting for Berkson error in exposure in ordinary and conditional logistic regression and in Poisson regression
BackgroundINTEROCC is a seven-country cohort study of occupational exposures and brain cancer risk, including occupational exposure to...
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Elucidating vaccine efficacy using a correlate of protection, demographics, and logistic regression
BackgroundVaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other...
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Bayesian multilevel multivariate logistic regression for superiority decision-making under observable treatment heterogeneity
BackgroundIn medical, social, and behavioral research we often encounter datasets with a multilevel structure and multiple correlated dependent...
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Assessment of Ki-67 expression levels in IDH-wildtype glioblastoma using logistic regression modelling of VASARI features
To investigate the value of using VASARI signs preoperatively to assess Ki-67 proliferation index levels in patients with IDH-wildtype glioblastoma...
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Machine-learning vs. logistic regression for preoperative prediction of medical morbidity after fast-track hip and knee arthroplasty—a comparative study
BackgroundMachine-learning models may improve prediction of length of stay (LOS) and morbidity after surgery. However, few studies include fast-track...
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Establishment of HIV-negative neurosyphilis risk score model based on logistic regression
ObjectiveTo establish the risk scoring model for HIV-negative neurosyphilis (NS) patients and to optimize the lumbar puncture strategy.
...
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Privacy-preserving logistic regression with secret sharing
BackgroundLogistic regression (LR) is a widely used classification method for modeling binary outcomes in many medical data classification tasks....
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Multiple logistic regression model to predict bile leak associated with subtotal cholecystectomy
BackgroundThere are no prediction models for bile leakage associated with subtotal cholecystectomy (STC). Therefore, this study aimed to generate a...
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Analysis and prediction of older adult sports participation in South Korea using artificial neural networks and logistic regression models
BackgroundKorea’s aging population and the lack of older adult participation in sports are increasing medical expenses.
AimsThis study aimed to...
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Multivariate logistic regression analysis of risk factors for birth defects: a study from population-based surveillance data
ObjectiveTo explore risk factors for birth defects (including a broad range of specific defects).
MethodsData were derived from the Population-based...
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Prediction of insomnia severity based on early maladaptive schemas: a logistic regression analysis
BackgroundIn spite of the major role of early maladaptive schemas in vulnerability to various psychological disorders, studies about the relationship...
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Predictive models for delay in medical decision-making among older patients with acute ischemic stroke: a comparative study using logistic regression analysis and lightGBM algorithm
ObjectiveTo explore the factors affecting delayed medical decision-making in older patients with acute ischemic stroke (AIS) using logistic...
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Determinants associated with internet gaming disorder in female medical students: a logistic regression analysis using a random sampling survey
BackgroundInternet gaming disorder (IGD) is a momentously growing issue of all ages, and medical students are not immune from the ever-increasing...
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Modern contraceptive method utilization and determinant factors among women in Ethiopia: Multinomial logistic regression mini- EDHS-2019 analysis
BackgroundGlobally, approximately 290,000 women between the ages of 15 and 49 died from pregnancy-related problems in 2014 alone, with these...
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Differential diagnosis of atypical and anaplastic meningiomas based on conventional MRI features and ADC histogram parameters using a logistic regression model nomogram
The purpose of the study was to determine the value of a logistic regression model nomogram based on conventional magnetic resonance imaging (MRI)...
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An analysis of factors influencing cognitive dysfunction among older adults in Northwest China based on logistic regression and decision tree modelling
BackgroundCognitive dysfunction is one of the leading causes of disability and dependence in older adults and is a major economic burden on the...
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Predictors of in-hospital mortality among patients with symptoms of stroke, Mashhad, Iran: an application of auto-logistic regression model
BackgroundStroke is the second leading cause of death in adults worldwide. There are remarkable geographical variations in the accessibility to...
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Development and validation of medical record-based logistic regression and machine learning models to diagnose diabetic retinopathy
PurposesMany factors were reported to be associated with diabetic retinopathy (DR); however, their contributions remained unclear. We aimed to...
