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Data-Driven Prognostication in Distal Medium Vessel Occlusions Using Explainable Machine Learning.
AJNR. American journal of neuroradiology
Apr 2, 2025
BACKGROUND AND PURPOSE: Distal medium vessel occlusions (DMVOs) are estimated to cause acute ischemic stroke in 25%-40% of cases. Prognostic models can inform patient counseling and research by enabling outcome predictions. However, models designed s...
Comprehensive Segmentation of Gray Matter Structures on T1-Weighted Brain MRI: A Comparative Study of Convolutional Neural Network, Convolutional Neural Network Hybrid-Transformer or -Mamba Architectures.
AJNR. American journal of neuroradiology
Apr 2, 2025
BACKGROUND AND PURPOSE: Recent advances in deep learning have shown promising results in medical image analysis and segmentation. However, most brain MRI segmentation models are limited by the size of their data sets and/or the number of structures t...
Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma.
Frontiers in immunology
Apr 2, 2025
BACKGROUND: Unlike lung adenocarcinoma, patients with advanced squamous carcinoma exhibit a low proportion of driver gene positivity, with fewer effective treatment strategies available. Chemoimmunotherapy has now become the standard first-line treat...
Identifying the Most Critical Predictors of Workplace Violence Experienced by Junior Nurses: An Interpretable Machine Learning Perspective.
Journal of nursing management
Apr 2, 2025
Workplace violence, defined as any disruptive behavior or threat to employees, seriously threatens junior nurses. Compared with senior nurses, junior nurses are more vulnerable to workplace violence due to inexperience, low professional recognition,...
Evaluating how different balancing data techniques impact on prediction of premature birth using machine learning models.
PloS one
Apr 2, 2025
Premature birth can be defined as birth before 37 weeks of gestation, which is a significant global health issue, being the main cause for neonatal deaths. In this work, we evaluate machine learning models for predicting premature birth using Brazili...
Understanding patterns of loneliness in older long-term care users using natural language processing with free text case notes.
PloS one
Apr 2, 2025
Loneliness and social isolation are distressing for individuals and predictors of mortality, yet data on their impact on publicly funded long-term care is limited. Using recent advances in natural language processing (NLP), we analysed pseudonymised ...
Development and validation of machine learning models for early diagnosis and prognosis of lung adenocarcinoma using miRNA expression profiles.
Cancer biomarkers : section A of Disease markers
Apr 2, 2025
ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using Machine learning（ML）algorithms, aiming to enhance clinical decision-making accuracy.MethodsData from The Cancer Genome Atlas (TCGA) for LUAD patients...
Computer vision and tactile glove: A multimodal model in lifting task risk assessment.
Applied ergonomics
Apr 1, 2025
Work-related injuries from overexertion, particularly lifting, are a major concern in occupational safety. Traditional assessment tools, such as the Revised NIOSH Lifting Equation (RNLE), require significant training and practice for deployment. This...
Deep learning for liver lesion segmentation and classification on staging CT scans of colorectal cancer patients: a multi-site technical validation study.
Clinical radiology
Apr 1, 2025
AIM: To validate a liver lesion detection and classification model using staging computed tomography (CT) scans of colorectal cancer (CRC) patients.
Multi-class brain malignant tumor diagnosis in magnetic resonance imaging using convolutional neural networks.
Brain research bulletin
Apr 1, 2025
Glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and brain metastases (BM) are common malignant brain tumors with similar radiological features, while the accurate and non-invasive dialgnosis is essential for selecting appropriate...
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