OBJECTIVE: Prognostication in patients with disorders of consciousness (DOCs) remains challenging because of heterogeneous etiologies, pathophysiologies and, consequently, highly variable electroencephalograms (EEGs). Here, we use EEG patterns that a...
International journal of psychology : Journal international de psychologie
Aug 1, 2025
The purpose of this study was to identify and rank the most important predictors of self-esteem. Data were drawn from the Midlife in the United States (MIDUS) study, a nationally representative survey of American adults. A total of 81 potential predi...
OBJECTIVE: To evaluate the impact of deep learning-based image conversion on the accuracy of automated coronary artery calcium quantification using thin-slice, sharp-kernel, non-gated, low-dose chest computed tomography (LDCT) images collected from m...
Sex estimation is an indispensable test for identifying skeletal remains in the field of forensic anthropology. We developed a novel sex-estimation method for skulls and several parts of the skull using machine learning. A total of 240 skull shapes w...
Ecotoxicology and environmental safety
Aug 1, 2025
Osteoporosis (OP) is a chronic progressive bone disease, and its occurrence and development under cadmium exposure remain unclear. This study aims to explore the role of cadmium exposure in the pathogenesis of OP through a comprehensive analysis of m...
Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, leads to significant alterations in brain structure. This study used machine learning (ML) to estimate brain age from structural MRI scans and investigate...
Clinical nutrition (Edinburgh, Scotland)
Aug 1, 2025
BACKGROUND: Artificial intelligence enables automated three-dimensional (3D) volumetric body composition (BC) analysis from computed tomography (CT), opposed to single third lumbar vertebra (L3) slices alone. This study aimed to identify relationship...
OBJECTIVES: Systemic sclerosis (SSc) is a complex autoimmune disease with both known and unidentified genetic contributors. While genome-wide association studies (GWAS) have implicated multiple loci, many reside in noncoding regions. We aimed to iden...
This study introduces a novel multimodal deep learning model tailored for the differentiation of benign and malignant breast masses using dual-view breast ultrasound images (radial and anti-radial views) in conjunction with corresponding radiology re...
AIMS: This study was to create an interpretable machine learning model to predict the risk of mortality within 90 days for ICU patients suffering from pressure ulcers.
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