Seoul National University Hospital researchers have developed an AI model that predicts the response to an anticonvulsant ...
One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...
de Filippis, R. and Al Foysal, A. (2026) Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data.
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Abstract: The increasing scale and complexity of remote sensing (RS) observations demand distributed processing to effectively manage the vast volumes of data generated. However, distributed ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Abstract: Deep learning models have shown impressive performance across a range of computer vision tasks. However, their lack of transparency limits their adoption in tasks where a clear understanding ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease, and if it is accurately predicted ...
A futuristic AI symbol hovers effortlessly, adorned with a bright red and white Christmas hat, blending holiday cheer with cutting-edge technology. The minimalist background accentuates the playful ...
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