Results 141 to 150 of about 120,140 (335)
Statistical Contrastive Learning for Spatio-Temporal Anomaly Detection
Anomaly detection is an interdisciplinary research area which attracts substantial attention both in statistics and in machine learning due to its critical role in a wide range of diverse applications, from cybersecurity to health monitoring.
Zhiwei Zhen, Yuzhou Chen, Yulia R. Gel
doaj +1 more source
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
A Theory-Driven Self-Labeling Refinement Method for Contrastive Representation Learning [PDF]
Pan Zhou +3 more
openalex +3 more sources
A Good View for Graph Contrastive Learning
Due to the success observed in deep neural networks with contrastive learning, there has been a notable surge in research interest in graph contrastive learning, primarily attributed to its superior performance in graphs with limited labeled data. Within
Xueyuan Chen, Shangzhe Li
doaj +1 more source
Metabolic and Microvascular Risk Factors Associated With Brain Health in Type 1 Diabetes
ABSTRACT We examined relationships between metabolic factors, microvascular complications, and brain health in adults with type 1 diabetes. Fifty‐one adults were assessed for metabolic risk factors, microvascular complications, and cognitive function, with a subset completing brain MRI.
Jihyun Park +7 more
wiley +1 more source
Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase‐7 (MMP‐7), and serum anti–malondialdehyde‐acetaldehyde (anti‐MAA) antibody for rheumatoid arthritis (RA)–associated interstitial lung disease (ILD) risk stratification.
Kelsey Coziahr +16 more
wiley +1 more source
Graph neural networks integrating contrastive learning have attracted growing attention in urban traffic flow forecasting. However, most existing graph contrastive learning methods do not perform well in capturing local–global spatial dependencies or ...
Lin Pan +3 more
doaj +1 more source
Self-Supervised ECG Anomaly Detection Based on Time-Frequency Specific Waveform Mask Feature Fusion
The imbalance of ECG signal data and the complexity of labeling pose significant challenges for deep learning-based anomaly detection. Traditional contrastive learning approaches for ECG anomaly detection often rely on reconstruction or generation ...
Chongrui Tian, Fengbin Zhang
doaj +1 more source
A Mathematical Perspective On Contrastive Learning
44 pages, 15 ...
Ricardo Baptista +2 more
openaire +2 more sources
Chatgpt Based Contrastive Learning for Radiology Report Summarization
Zuowei Jiang +4 more
openalex +1 more source

