AIMC Topic: Algorithms

Clear Filters Showing 5121 to 5130 of 28713 articles

Adaptive multi-graph contrastive learning for bundle recommendation.

Neural networks : the official journal of the International Neural Network Society
Recently, recommending bundles - sets of items that complement each other - instead of individual items to users has drawn much attention in both academia and industry. Models based on Graph Neural Networks (GNNs) for bundle recommendation have achie...

Noise-resistant sharpness-aware minimization in deep learning.

Neural networks : the official journal of the International Neural Network Society
Sharpness-aware minimization (SAM) aims to enhance model generalization by minimizing the sharpness of the loss function landscape, leading to a robust model performance. To protect sensitive information and enhance privacy, prevailing approaches add...

Deep learning corrects artifacts in RASER MRI profiles.

Magnetic resonance imaging
A newly developed magnetic resonance imaging (MRI) approach is based on "Radiowave amplification by the stimulated emission of radiation" (RASER). RASER MRI potentially allows for higher resolution, is inherently background-free, and does not require...

Diagnostic accuracy of deep learning-based algorithms in laryngoscopy: a systematic review and meta-analysis.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Laryngoscopy is routinely used for suspicious vocal cord lesions with limited performance. Accumulated studies have demonstrated the bright prospect of deep learning in processing medical imaging. In this study, we perform a systematic revie...

GDMol: Generative Double-Masking Self-Supervised Learning for Molecular Property Prediction.

Molecular informatics
BACKGROUND: Effective molecular feature representation is crucial for drug property prediction. Recent years have seen increased attention on graph neural networks (GNNs) that are pre-trained using self-supervised learning techniques, aiming to overc...

Laboratory Data as a Potential Source of Bias in Healthcare Artificial Intelligence and Machine Learning Models.

Annals of laboratory medicine
Artificial intelligence (AI) and machine learning (ML) are anticipated to transform the practice of medicine. As one of the largest sources of digital data in healthcare, laboratory results can strongly influence AI and ML algorithms that require lar...

Robust brain MRI image classification with SIBOW-SVM.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Primary Central Nervous System tumors in the brain are among the most aggressive diseases affecting humans. Early detection and classification of brain tumor types, whether benign or malignant, glial or non-glial, is critical for cancer prevention an...

Enabling machine learning models in alarm fatigue research: Creation of a large relevance-annotated oxygen saturation alarm data set.

Computers in biology and medicine
BACKGROUND: Too many unnecessary alarms in the intensive care unit are one of the main reasons for alarm fatigue: Medical staff is overburdened and fails to respond appropriately. This endangers both patients and staff. Currently, there are no algori...