openheart.bmj

Risk prediction modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: leveraging machine learning

Background Preprocedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and benchmarking hospital performance. This study ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
Frontiers

Enabling rapid and accurate grand discrimination of flue-cured tobacco: a near-infrared hyperspectral and machine learning approach

To address the inefficiency and subjectivity of manual grading, this study established a machine learning model based on near-infrared hyperspectral data (950–1650 nm) for the accurate classification ...
IEEE

Residual Compensation of the Articulated Arm Coordinate Measuring Machine Based on Extreme Learning Machine Optimized by Sparrow Search Algorithm

Abstract: Kinematic calibration is essential for improving the accuracy of Articulated Arm Coordinate Measuring Machines (AACMMs). However, even after calibration, residual errors can significantly ...
IEEE

Application of Evolutionary Algorithms to Enhance the Efficiency of Neural Networks and Machine Learning Algorithms

Abstract: This study examines approaches to hyperparameter optimization in machine learning and deep learning systems using genetic algorithms. Today, the success of neural networks and machine ...