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 ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Enhanced prediction capability: Machine learning-based system matches and in some cases outperforms traditional forecasting systems, with particular improvements in northern Europe where conventional ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...