A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
The ability to predict wildfires - such as those that recently devastated Los Angeles and Canada - is advancing rapidly with the help of ML–driven high-quality data. A new paper, published today ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
A new technical paper titled “Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate” was published by researchers at KTH Royal Institute of Technology and ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
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 ...
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