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Machine learning-based integration reveals immunological heterogeneity and the clinical potential of T cell receptor (TCR) gene pattern in hepatocellular carcinoma.
Apoptosis : an international journal on programmed cell death
Feb 4, 2025
The T Cell Receptor (TCR) significantly contributes to tumor immunity, whereas the intricate interplay with the Hepatocellular Carcinoma (HCC) microenvironment and clinical significance remains largely unexplored. Here, we aimed to examine the functi...
Deep learning opportunistic screening for osteoporosis and osteopenia using radiographs of the foot or ankle - A pilot study.
European journal of radiology
Feb 4, 2025
BACKGROUND: The gold standard method for diagnosing low bone mineral density (BMD) is using dual-energy X-ray absorptiometry (DXA) however, most patients with low BMD are often not screened. We aimed to create a deep learning (DL) model to screen for...
Automated detection of early-stage osteonecrosis of the femoral head in adult using YOLOv10: Multi-institutional validation.
European journal of radiology
Feb 4, 2025
OBJECTIVES: To develop a deep learning model based on the You Only Look Once version 10 (YOLOv10) for detecting early-stage ONFH in adult using radiographs.
Machine learning for predicting severe dengue in Puerto Rico.
Infectious diseases of poverty
Feb 4, 2025
BACKGROUND: Distinguishing between non-severe and severe dengue is crucial for timely intervention and reducing morbidity and mortality. World Health Organization (WHO)-recommended warning signs offer a practical approach for clinicians but have limi...
Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults utilizing SHAP: a study based on NHANES 2015-2018.
BMC public health
Feb 4, 2025
BACKGROUND: Alveolar bone loss (ABL) is common in modern society. Heavy metal exposure is usually considered to be a risk factor for ABL. Some studies revealed a positive trend found between urinary heavy metals and periodontitis using multiple logis...
Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.
BMC medical imaging
Feb 4, 2025
BACKGROUND: Computed tomography attenuation correction (CTAC) is commonly used in cardiac SPECT imaging to reduce soft-tissue attenuation artifacts. However, CTAC is prone to inaccuracies due to CT artifacts and SPECT-CT mismatch, along with addition...
Machine learning-random forest model was used to construct gene signature associated with cuproptosis to predict the prognosis of gastric cancer.
Scientific reports
Feb 4, 2025
Gastric cancer (GC) is one of the most common tumors; one of the reasons for its poor prognosis is that GC cells can resist normal cell death process and therefore develop distant metastasis. Cuproptosis is a novel type of cell death and a limited nu...
Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques.
Scientific reports
Feb 4, 2025
In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging-reporting and data system (PI-RA...
Automatic cervical lymph nodes detection and segmentation in heterogeneous computed tomography images using deep transfer learning.
Scientific reports
Feb 4, 2025
To develop a deep learning model using transfer learning for automatic detection and segmentation of neck lymph nodes (LNs) in computed tomography (CT) images, the study included 11,013 annotated LNs with a short-axis diameter ≥ 3 mm from 626 head an...
Risk prediction of functional disability among middle-aged and older adults with arthritis: A nationwide cross-sectional study using interpretable machine learning.
International journal of orthopaedic and trauma nursing
Feb 4, 2025
BACKGROUND: Arthritis is a common chronic disease among middle-aged and older adults and is strongly related to functional decline.
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