Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.
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 ...
A new Fracture Risk Assessment Tool that includes bone microarchitecture measures outperformed the current tool that uses ...
New research presented during the 2024 San Antonio Breast Cancer Symposium (SABCS) reveals a new machine learning model that could change the way metastatic breast cancer is treated in the future. By ...
Sparse early-stage data limits accurate geological risk assessment, increasing the chance of undetected hazards ahead of the TBM. By integrating borehole-derived information through an observation ...
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 ...
Risk management within construction has always been a moving target. Today's projects demand proactive strategies due to ...
Artificial intelligence (AI) and machine learning are increasingly being used in healthcare, raising hopes that technology could help identify people at risk of suicide and self-harm earlier than ever ...
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