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Machine learning model may provide an earning warning of preeclampsia in late gestation

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy.
IEEE

Neural-XGBoost: A Hybrid Approach for Disaster Prediction and Management Using Machine Learning

Abstract: Effective disaster prediction is essential for disaster management and mitigation. This study addresses a multi-classification problem and proposes the Neural-XGBoost disaster prediction ...
Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
IEEE

Improving Accuracy in Human Voice Recognition for Gender Classification Using Machine Learning Algorithms

Abstract: This study focused on improving the accuracy of human voice recognition, specifically for distinguishing between male and female voices, by comparing two algorithms. The Random Forest ...