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Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning.
Geospatial health
Mar 26, 2025
INTRODUCTION: Chronic Obstructive Pulmonary Disease (COPD) mortality rates and global warming have been in the focus of scientists and policymakers in the past decade. The long-term shifts in temperature and weather patterns, commonly referred to as ...
Nutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach.
PloS one
Mar 26, 2025
Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permanent disability and stigma. Described as a disease of poverty, the impact of socioeconomic indicators ...
Artificial intelligence in dysphagia assessment: evaluating lingual muscle composition in head and neck cancer.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Mar 25, 2025
PURPOSE: Oropharyngeal dysphagia is a common and debilitating condition in head and neck cancer (HNC) patients. This study aimed to evaluate the relationship between tongue muscle composition (quantity and quality) and the risk of dysphagia in non-su...
Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohort.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 25, 2025
PURPOSE: Information on deep learning (DL) tumor segmentation accuracy on a voxel and a structure level is essential for clinical introduction. In a previous study, a DL model was developed for oropharyngeal cancer (OPC) primary tumor (PT) segmentati...
Preoperative Prediction of STAS Risk in Primary Lung Adenocarcinoma Using Machine Learning: An Interpretable Model with SHAP Analysis.
Academic radiology
Mar 25, 2025
BACKGROUND: Accurate preoperative prediction of spread through air spaces (STAS) in primary lung adenocarcinoma (LUAD) is critical for optimizing surgical strategies and improving patient outcomes.
A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.
Neurology
Mar 25, 2025
BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do not show cognitive decline over 80 weeks of follow-up. Identifying and excluding these individuals can increase power to detect treatment effects. We...
Ensemble network using oblique coronal MRI for Alzheimer's disease diagnosis.
NeuroImage
Mar 25, 2025
Alzheimer's disease (AD) is a primary degenerative brain disorder commonly found in the elderly, Mild cognitive impairment (MCI) can be considered a transitional stage from normal aging to Alzheimer's disease. Therefore, distinguishing between normal...
Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Cancer Detection.
Medicina (Kaunas, Lithuania)
Mar 25, 2025
: Breast cancer (BC) is the most common type of cancer in women, accounting for more than 30% of new female cancers each year. Although various treatments are available for BC, most cancer-related deaths are due to incurable metastases. Therefore, th...
Convolutional Neural Network Models for Visual Classification of Pressure Ulcer Stages: Cross-Sectional Study.
JMIR medical informatics
Mar 25, 2025
BACKGROUND: Pressure injuries (PIs) pose a negative health impact and a substantial economic burden on patients and society. Accurate staging is crucial for treating PIs. Owing to the diversity in the clinical manifestations of PIs and the lack of ob...
Thyroid nodule classification in ultrasound imaging using deep transfer learning.
BMC cancer
Mar 25, 2025
BACKGROUND: The accurate diagnosis of thyroid nodules represents a critical and frequently encountered challenge in clinical practice, necessitating enhanced precision in diagnostic methodologies. In this study, we investigate the predictive efficacy...
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