Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 27, 2025
Alzheimer's disease (AD) is the most common neurodegenerative disorder, yet its underlying mechanisms remain elusive. Early and accurate diagnosis is crucial for timely intervention and disease management. In this paper, a multi-strategy improved dun...
Computer methods and programs in biomedicine
Apr 26, 2025
BACKGROUND AND OBJECTIVE: Endometriosis is a chronic gynecological condition known to affect the quality of life of millions of women globally, often manifesting with symptoms that impact sleep quality. Emerging evidence suggests a crucial role of th...
Asthma is a reversible disease characterized by airflow limitation and chronic airway inflammation. Previous neuroimaging studies have shown structural and functional abnormalities in the brains of individuals with asthma. However, earlier research h...
Neural networks : the official journal of the International Neural Network Society
Apr 25, 2025
For the multi-class classification problems, we propose a new probabilistic output classifier called kernel-free quadratic surface support vector machine for conditional probability estimation (CPSQSVM), which is based on a newly developed binary cla...
Breast cancer is one of the leading causes of death and morbidity among women worldwide. Identifying cancerous cells remains a complex and time-consuming task, particularly when performed manually by radiologists or pathologists, contributing to high...
INTRODUCTION: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. Machine learning offers powerful tools...
Diabetes mellitus stands out as one of the most prevalent chronic conditions affecting pediatric populations. The escalating incidence of childhood type 1 diabetes (T1D) globally is a matter of increasing concern. Developing an effective model that l...
The study aims to assess the efficacy of various neural network architectures in predicting the National Early Warning Systems (NEWS) score, using vital signs, to enhance early warning and monitoring in clinical settings. A comparative evaluation o...
The ambulance dispatch system plays a crucial role in emergency medical care by ensuring efficient communication, reducing response times, and ultimately saving lives. Delays in ambulance arrival can have serious consequences for patient health and s...
This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. The goal is to evaluate the effectiveness and performance of these models in accurately identifying epilepti...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.