Dioxin-like pollutants, especially 2,3,7,8-Tetrachlorodibenzo-p-dioxin, are recognized human carcinogens. Retrospective studies suggest a link between dioxins and soft tissue sarcomas, including liposarcoma, but mechanisms remain unclear. This study ...
The key objective of producing artificial digital data is to closely mimic real data. However, because of improper use by malevolent users, the legitimacy of this kind of digital content may be under threat in society. Deepfake techniques, which repl...
Chronic diseases are highly prevalent among older adults and may be associated with their ability to achieve successful aging, which encompasses five key components: absence of major chronic diseases, freedom from disability, high cognitive function,...
This data descriptor introduces a dataset designed for affective computing applications in the context of human-computer interaction, with a particular focus on user experience (UX) and website interactions. The dataset comprises interaction logs, in...
Accurate and early diagnosis of malaria from peripheral blood smear images remains a critical challenge in healthcare, particularly in resource-limited settings. In this work, we propose an optimized convolutional neural network (CNN) framework enhan...
Pneumonia is a severe respiratory ailment that may be caused by viruses, fungus, and bacteria. Pneumonia causes the accumulation of water, purulent material, or other fluids in the air sacs (alveoli) of the lungs. A delay in the identification of pne...
Despite advancements in modern healthcare, diabetes mellitus remains a lifelong, incurable condition. Empowering patients through health education and self-management is essential in preventing disease progression. This study evaluates the effectiven...
Skin cancer is among the most widely distributed, deadliest cancers around the globe, and early diagnosis becomes vital to enhance patient survival. Deep learning has demonstrated high potential for automatic skin lesion classification. However, exis...
Sports injury prediction is crucial for university football player health, yet existing research predominantly focuses on professional athletes and lacks interpretability. Using the Kaggle "University Football Injury Prediction Dataset" (800 Chinese ...
This study proposes a novel machine learning (ML)-based stacking technique that integrates Single Nucleotide Polymorphisms (SNPs) and inferred local ancestry (LA) to improve predictive accuracy in clinical outcomes. Asthma, particularly severe asthma...
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