The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...
According to the authors, incorporating a broad spectrum of biomarkers allows the models to reflect the continuous and ...
Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how ...
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
University of Idaho receives over $6M in DoD grants to advance machine learning research for PTSD diagnosis and military ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
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