As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
This project focuses on building and evaluating machine learning (ML) classification models to predict whether a person has diabetes based on medical and demographic features. It was developed as an ...
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
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 ...
Abstract: Skin cancer affects over 2 million people worldwide each year. Although dermoscopy is the gold standard screening technique, it only assesses the superficial features of skin lesions. Novel ...
Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results