Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...
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 ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
IEEE Spectrum on MSN
Machine learning system monitors patient pain during surgery
To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...
Electrical power systems engineers need practical methods for predicting solar output power under varying environmental conditions of a single panel. By integrating an Arduino-based real-time data ...
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