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Construction of a prognostic signature based on T-helper 17 cells differentiation-related genes for predicting survival and tumor microenvironment in head and neck squamous cell carcinoma.
Medicine (Baltimore)
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Department of Otolaryngology, Hangzhou Red Cross Hospital (Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine), Hangzhou, Zhejiang, China.
T-helper 17 (Th17) cells significantly influence the onset and advancement of malignancies. This study endeavor focused on delineating molecular classifications and developing a prognostic signature grounded in Th17 cell differentiation-related genes (TCDRGs) using machine learning algorithms in head and neck squamous cell carcinoma (HNSCC). A consensus clustering approach was applied to The Cancer Genome Atlas-HNSCC cohort based on TCDRGs, followed by an examination of differential gene expression using the limma package.
View Article and Find Full Text PDFDelta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.
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Machine Learning Department, H. Lee Moffit Cancer Center and Research Institute, Tampa, FL.
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Department of Radiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings for rib fractures (RFs) detection on CT images. This study included 243 consecutive chest trauma patients (mean age, 58.1 years; female, 166) with rib CT scans.
View Article and Find Full Text PDFSocial mates dynamically coordinate aggressive behavior to produce strategic territorial defense.
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Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, Rhode Island, United States of America.
Negotiating social dynamics among allies and enemies is a complex problem that often requires individuals to tailor their behavioral approach to a specific situation based on environmental and/or social factors. One way to make these contextual adjustments is by arranging behavioral output into intentional patterns. Yet, few studies explore how behavioral patterns vary across a wide range of contexts, or how allies might interlace their behavior to produce a coordinated response.
View Article and Find Full Text PDFRadar versus optical: The impact of cloud cover when mapping seasonal surface water for health applications in monsoon-affected India.
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UK Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, United Kingdom.
Surface water plays a vital role in the spread of infectious diseases. Information on the spatial and temporal dynamics of surface water availability is thus critical to understanding, monitoring and forecasting disease outbreaks. Before the launch of Sentinel-1 Synthetic Aperture Radar (SAR) missions, surface water availability has been captured at various spatial scales through approaches based on optical remote sensing data.
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