Neuroscience News

Young People Turn to AI for Mental Health Support

Analyzing data from the 2024–2025 Healthy Minds Study, the research team discovered that while 18% of the general college ...
Scientific Research Publishing

McCauley, S. (2012) Applying Multinomial Logistic Regression to Categorize Student Technological Knowledge Based on Technology Usage Attributes. Walden University.

ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
Scientific Research Publishing

Li, L., Rysavy, M.A., Bobashev, G. and Das, A. (2024) Comparing Methods for Risk Prediction of Multicategory Outcomes: Dichotomized Logistic Regression Vs. Multinomial Logit ...

ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
Frontiers

Multimorbidity patterns are associated with postoperative delirium in older patients undergoing non-cardiac surgery: an observational study

Multimorbidity is associated with adverse outcomes among older adult surgical patients, yet its role in postoperative delirium (POD) remains unclear. In the present study, we hypothesized that ...
LinkedIn

How to Decide Between Multinomial and Ordinal Logistic Regression Models

A great tool to have in your statistical tool belt is logistic regression. It comes in many varieties and many of us are familiar with the variety for binary outcomes. But multinomial and ordinal ...
BMJ

Burden of abnormal nutritional indices among women aged 15–24 years in 40 low-income and middle-income countries: a multilevel multinomial logistic regression analysis

Background Despite global efforts to improve nutrition, young women aged 15–24 years in low-income and middle-income countries (LMICs) face persistent dual burdens of malnutrition, marked by high ...
IEEE

Comparative Analysis of Sparse Multinomial Logistic Regression and Convolutional Neural Networks for Multi-Class Image Classification

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
ahajournals.org

Development of a Risk Tracking Model for Neurological Deterioration in Ischemic Stroke Based on Blood Pressure Dynamics

Using the significant link between blood pressure fluctuations and neurological deterioration (ND) in patients with ischemic stroke, this study aims to develop a predictive model capable of tracking ...
LinkedIn

Logistic Regression Models for Multinomial and Ordinal Variables

The multinomial (a.k.a. polytomous) logistic regression model is a simple extension of the binomial logistic regression model. They are used when the dependent variable has more than two nominal ...
SciELO

Effect of indices on desertification risk: spatial and hierarchical approach using multinomial logistic regression

Desertification is the degradation process caused by climatic conditions and human activities that results in loss of soil productivity and decline in vegetation growth in the long term. Several ...
The Lancet

Corrigendum to—“Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model” [eBioMedicine 102(2024) 105085]

aDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA bDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA ...
The Lancet

Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model

aDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA bDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA ...