Abstract: In the clinic, brain tumor detection and semantic segmentation are critical tasks in medical image analysis, particularly in magnetic resonance imaging (MRI), which assists clinicians in ...

Abstract: The automated identification of wood surface defects is crucial for maintaining product quality and maximizing resource efficiency in the timber industry. Yet, conventional deep learning ...

This standalone MATLAB project generates edge groups from images, converts manual polyline annotations into edge-group labels, and trains RF and PCA/SVM classifiers. The repository includes the ...

Summary: Researchers introduced a deep-learning artificial intelligence capable of predicting the molecular classification of brain and spinal cord tumors in minutes using standard, universally ...

How do software developers respond when they come across code they do not intuitively understand? Neuropsychologists have now explored this question by recording brain activity alongside eye movements ...

This review aims to identify the key barriers to clinical application of Machine Learning (ML) in multi-class voice disorder classification. A comprehensive scoping review of research published ...

Expression patterns of circulating microRNAs in classification models: New opportunities in brain tumor diagnosis. This is an ASCO Meeting Abstract from the 2026 ASCO Annual Meeting I. This abstract ...