BMJ Open

Shift work sleep disorder and associated factors among healthcare professionals working at Jimma University Medical Center, Southwest Ethiopia, 2022: a cross-sectional study

Objectives Shift work sleep disorder is a circadian rhythm sleep-wake disorder characterised by insomnia and/or excessive sleepiness associated with a shift work schedule that overlaps with habitual ...
RMD Open

Systemic lupus erythematosus damage risk index (SLE-DRI): a simple machine learning-based tool for identifying patients at risk for early organ damage

Objective Organ damage is a key determinant of poor prognosis and increased mortality in systemic lupus erythematosus (SLE).
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 ...

Can AI detect hedgehogs from space? Maybe if you find brambles first.

Rather than searching for the hedgehogs directly, researcher Gabriel Mahler developed an AI model that identifies brambles, ...
Scientific Research Publishing

Assessing the Socio-Economic Impact of Solid-Waste Pollution on Local Communities and Tourism at Kigamboni Beach, Dar es Salaam ()

Solid-waste pollution is reshaping the social and economic landscape of urban shorelines, yet its livelihood costs remain ...
Lupus Science & Medicine

Breastfeeding determinants in Egyptian mothers with systemic lupus erythematosus or rheumatoid arthritis: a retrospective cohort study

Objective Breastfeeding prevalence and challenges among women of systemic lupus erythematosus (SLE) and rheumatoid arthritis ...
Scientific Research Publishing

Evaluating Utility of Machine Learning-Based Imputation Methods to Account for Attrition in Multi-Stage Epilepsy Prevalence Surveys ()

1 Department of Mathematics, University of Nairobi, Nairobi, Kenya. 2 African Population and Health Research Center, Nairobi, Kenya. 3 Department of Psychiatry, University of Oxford, Oxford, United ...
Frontiers

Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients

Background: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD). Methods: Patients with T2DM who underwent ...
IEEE

Transformer fault diagnosis method based on multi-classification logistic regression

Abstract: Transformer is the core equipment in power system, its running state directly affects the safety and economy of power grid. Traditional transformer fault diagnosis methods often rely on ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
ascopubs.org

Performance of Two-Phase Designs for the Time-to-Event Outcome and a Case Study Assessing the Relapse Risk Associated With B-ALL Subtypes

As biomarker studies employ increasingly complex and expensive genomics and other correlative methods, it is increasingly important to rigorously design these studies and analyze the downstream ...
The Lancet

Prediction of mammographic breast density based on clinical breast ultrasound images using deep learning: a retrospective analysis

aDepartment of Information and Computer Sciences, University of Hawaiʻi at Mānoa, POST Bldg, 1860 East-West Rd, Honolulu, HI, 96822, USA bUniversity of Hawaiʻi Cancer Center, 701 Ilalo St, Honolulu, ...