New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...
Researchers have unveiled an interpretable, lightweight AI text detection framework using classical machine learning models that achieves near-perfect accuracy while lowering computational costs.
Researchers conducted a systematic review to assess the risk of bias and applicability of prediction models for fear of recurrence in patients with cancer.
Machine learning can sound pretty complicated, right? Like something only super-smart tech people get. But honestly, it’s ...
Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...
Trained on historical consumption data spanning a decade, the model demonstrated strong predictive performance. It achieved a training error of 0.182 and a forecasting accuracy of 95.2 percent, ...
ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...
EXtreme Gradient Boosting (XGBoost), a machine learning model, outperformed more traditional methods for predicting composite major adverse events (MAEs) and many individual events in patients ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
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