Artificial Intelligence Medical Compendium

There is a growing need to automate EEG monitoring of preterm-born infants, particularly where expert evaluation is limited. However, existing models necessitate human intervention for comprehensive assessment, thereby limiting the clinical applicabi... read more 

Zoonotic viral spillover represents a major global health challenge arising from complex interactions among viral evolution, reservoir ecology, host biology, environmental disruption, and human activities. Successful emergence requires viruses to ove... read more 

BACKGROUND: Residual cardiovascular risk remains substantial in patients with established coronary artery disease despite contemporary secondary prevention strategies. Conventional approaches focused on isolated risk factors may fail to capture the m... read more 

BACKGROUND: Atrial fibrillation (AF) recurrence after catheter ablation remains common, with recurrence rates up to 45%. Traditional risk scores demonstrate only modest predictive performance. Machine learning (ML) approaches have shown promise in im... read more 

Imaging biomarkers in magnetic resonance imaging (MRI) are important tools for diagnosing, tracking and treating Alzheimer's disease (AD). Neurofibrillary tau pathology in AD is closely linked to neurodegeneration and generally follows a pattern of s... read more 

This study aimed to develop a machine learning (ML) model combining radiomic signatures from subcortical structures on T1-weighted MR images with peripheral blood biomarkers to distinguish depressed patients with versus without a history of suicide a... read more 

Rare earth elements (REE) are increasingly mobilised from mine residues and other industrial sources, creating a need for rapid screening of chemically complex waters where conventional ICP-based analysis is impractical on site. Here, we evaluate a l... read more 

The integration of Artificial Intelligence (AI) across all professional and social spheres, and especially in the healthcare context, is transforming the way processes are carried out. In the field of clinical nursing, the use of AI-based techniques ... read more 

Understanding how active pharmaceutical ingredients (APIs) influence tablet disintegration remains essential for optimising oral drug product performance. In this work, we present an integrated, data-driven framework that combines deep-learning-based... read more 

BACKGROUND: Analysing motor imagery EEG signals using conventional Euclidean feature computation is challenging due to low spatial resolution, non-stationarity, and complex inter-channel dependencies, which limit robust subject-independent generaliza... read more