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 ...
Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Multicentric evaluation of an artificial intelligence model to stratify stage II colon cancer patients from whole slide images.
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...
ICU patients’ needs can change rapidly. The AI studies each patient to make personalized nutrition predictions. In A Nutshell ...
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