AIMC Topic: Databases, Factual

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EndoCompass project: endocrine laboratory medicine.

European journal of endocrinology
BACKGROUND: Endocrine science remains underrepresented in European Union research programmes despite the fundamental role of hormone health in human wellbeing. Analysis of the CORDIS database reveals a persistent gap between the societal impact of en...

Multi-View Self-Supervised Learning Enhances Automatic Sleep Staging From EEG Signals.

IEEE transactions on bio-medical engineering
Deep learning-based methods for automatic sleep staging offer an efficient and objective alternative to costly manual scoring. However, their reliance on extensive labeled datasets and the challenge of generalization to new subjects and datasets limi...

JailbreakHunter: A Visual Analytics Approach for Jailbreak Prompts Discovery From Large-Scale Human-LLM Conversational Datasets.

IEEE transactions on visualization and computer graphics
Large Language Models (LLMs) have gained significant attention but also raised concerns due to the risk of misuse. Jailbreak prompts, a popular type of adversarial attack towards LLMs, have appeared and constantly evolved to breach the safety protoco...

Feature Selection in Healthcare Datasets: Towards a Generalizable Solution.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: The increasing dimensionality of healthcare datasets presents major challenges for clinical data analysis and interpretation. This study introduces a scalable ensemble feature selection (FS) strategy optimized for multi-biom...

`Probabilistic ensemble learning for prediction of stroke thrombectomy outcomes from the NeuroVascular Quality Initiative-Quality Outcomes Database (NVQI-QOD) Acute Ischemic Stroke Registry.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
INTRODUCTION: Mechanical Thrombectomy (MT) is the standard of care in the interventional management of Acute Ischemic Stroke (AIS). The NVQI-QOD registry records detailed patient characteristics, pre-operative imaging, procedure metrics, and post-ope...

Enhancing automatic multilabel diagnosis of electrocardiogram signals: A masked transformer approach.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Electrocardiogram (ECG) is one of the most important diagnostic tools in clinical applications. Although deep learning models have been widely applied to ECG classification tasks, their accuracy remains limited, especially i...

Generative adversarial network augmented data for improved heart sound abnormality detection.

Computers in biology and medicine
The PhysioNet/Computing in Cardiology (CinC) Challenge 2016 dataset has driven significant advancements in automated heart sound analysis using machine learning (ML) and deep learning (DL). However, these efforts are constrained by the dataset's limi...

Integrating multi-source data for skin burn classification using deep learning.

Computers in biology and medicine
BACKGROUND: Skin burns result from thermal or chemical damage to the skin, requiring timely and accurate assessment for effective treatment. Determining the degree of burns is crucial for appropriate clinical decisions, especially for interventions l...

Digital pesticide: a comprehensive pesticide information database with dynamic web platform for artificial intelligence applications.

Pest management science
BACKGROUND: Pesticides are crucial for protecting crops from pests and diseases to meet the growing global food demand. In the era of artificial intelligence (AI), computer-aided approaches have the potential to significantly enhance the efficiency a...