A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...
Artificial Intelligence (AI) and Machine Learning (ML) in pediatrics represent a burgeoning field within healthcare, driven ...
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...
Metabolic-associated steatotic liver disease (MASLD) is a clinically heterogeneous condition with highly variable outcomes affecting more than 30% ...
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A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
Researchers from several Parisian institutions have worked together to develop a non-destructive approach to study how ...
Published in the journal Fire, the study titled “Artificial Intelligence for Geospatial Decision Support in Rural Wildfire Management: A Configurational Mapping Review” provides a systematic analysis ...
Abstract: In the poultry food industry, eggshell color is recognized as a crucial quality indicator that influences consumer preference and market value. Traditional classification methods, such as ...
Spatial reasoning is essential for solving complex tasks in dynamic and high-dimensional environments. However, current training models for spatial tasks are computationally demanding and heavily ...
Abstract: Lung diseases, such as COPD, lung cancer and pulmonary fibrosis remain leading causes of global morbidity and mortality, and require innovative solutions to early detection and prevention.
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