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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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Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
ObjectiveWith the ongoing evolution of the healthcare system and shifts in cultural paradigms, there is a pressing need to delve into the medical...
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Utilization of reproductive health services among undergraduate regular class students in Assosa University, BGRS: a comparison among three varieties of multilevel binary logistic regression models
IntroductionReproductive health service (RHS) helps for people to have a delighted and safe sex through their life journey. It enables especially for...
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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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Factors affecting the location of sphenoid sinus ostium: a binary logistic regression analysis
BackgroundSphenoid sinus is a type of sinus surrounded by critical structures so that its injury potential to induce complications during surgery....
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Impact of ignoring sampling design in the prediction of binary health outcomes through logistic regression: evidence from Malawi demographic and health survey under-five mortality data; 2000-2016
The birth and death rates of a population are among the crucial vital statistics for socio-economic policy planning in any country. Since the...
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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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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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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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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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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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Adjustment for baseline characteristics in randomized trials using logistic regression: sample-based model versus true model
BackgroundAdjustment for baseline prognostic factors in randomized clinical trials is usually performed by means of sample-based regression models....
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The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model
PurposeTo compare machine learning (ML) models with logistic regression model in order to identify the optimal factors associated with...
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Alternatives to Logistic Regression Models when Analyzing Cluster Randomized Trials with Binary Outcomes
Binary outcomes are often encountered when analyzing cluster randomized trials (CRTs). A common approach to obtaining the average treatment effect of...
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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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An empirical evaluation of approximate and exact regression-based causal mediation approaches for a binary outcome and a continuous or a binary mediator for case-control study designs
BackgroundIn the causal mediation analysis framework, several parametric regression-based approaches have been introduced in past years for...
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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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Determinants of coexistence of stunting, wasting, and underweight among children under five years in the Gambia; evidence from 2019/20 Gambian demographic health survey: application of multivariate binary logistic regression model
BackgroundMalnutrition happens when there are insufficient amounts of nutrients and energy consumed improperly. Included are both undernutrition and...
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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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Incorporation of CEUS and SWE parameters into a multivariate logistic regression model for the differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules
PurposeTo investigate the diagnostic value of contrast-enhanced ultrasound (CEUS) quantitative analysis parameters combined with shear wave...
