A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

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 ...

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Mass General ...

Machine learning models, particularly LightGBM, effectively predict hyperlipidemia in PLWH on HAART for six months, with high accuracy and area under curve values. The study's limitations include ...

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...

Krishnam Narsepalle argues traditional credit systems must evolve into event-driven architectures for real-time risk ...