Nuffield Trust

What’s shaping public satisfaction and dissatisfaction with the NHS?

The results of the British Social Attitudes survey earlier this year revealed that just a fifth of the British public were ...
BMJ Global Health

The Ethiopian Surgical Outcome Study (Ethio-SOS): a 7-day multicentre national prospective observational cohort study

Introduction Safe surgical care is a cost-effective intervention for addressing a wide range of conditions, yet postoperative ...
Scientific Research Publishing

An Accessible Predictive Model for Alzheimer’s Disease Based on Cognitive and Neuropathological Integration ()

Li, Y. and Liu, J. (2025) An Accessible Predictive Model for Alzheimer’s Disease Based on Cognitive and Neuropathological ...
IEEE

Maximum Likelihood for Logistic Regression Model With Incomplete and Hybrid-Type Covariates

Abstract: Logistic regression is a fundamental and widely used statistical method for modeling binary outcomes based on covariates. However, the presence of missing data, particularly in settings ...
Scientific Research Publishing

Ordinal Logistic Regression Model in Determining Factors Associated with Household Food Insecurity in Namibia ()

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...
IEEE

Predicting Block Delays in Bitcoin Blockchain via Bayesian and Non-Bayesian Logistic Regression

Abstract: Blockchain has found many uses beyond cryptocurrency trading. However, this technology faces the challenge of low transactions per second (TPS), which hinders it from competing at scale with ...
Frontiers

Risk factors associated with severe progression of Parkinson’s disease: random forest and logistic regression models

1 Department of Neurology, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China 2 Support Centre, Hubei No. 3 People’s Hospital of Jianghan University, Wuhan, China Background and aim: ...
Frontiers

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.