BACKGROUND: Machine learning shows great potential in science but struggles with complex, high-dimensional multi-omics data. PD progression is long, diagnosed mainly by clinical signs. This paper proposes a novel decision fusion method to improve the...
BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) remains a critical condition associated with high mortality rates, prolonged hospitalization, and reduced quality of life despite advances in critical care. The albumin-corrected anion gap (ACAG)...
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major driver of coronary artery disease (CAD). Prior studies often conflate T2DM- and CAD-specific metabolic alterations, limiting insights into CAD pathogenesis in T2DM. This study aimed to distinguis...
Epistemic emotions, and in particular curiosity, seem to enhance memory for both the specific information that stimulates the individual's curiosity and information presented in close temporal proximity. Most studies on memory and curiosity have adop...
Numerical variations and transitional anatomy in the human vertebral column represent a significant yet understudied aspect of skeletal development with potential effects on multiple physiological systems. Utilising UK Biobank data, we integrated gen...
The cerebellar vermis undergoes diverse structural changes with aging, yet region-specific aging patterns remain underexplored. Using Brain Structure Age (BSA), a deep learning biomarker from structural magnetic resonance imaging (MRI), we aimed to: ...
In an era of Generative Artificial Intelligence (AI), it may be possible to capitalise on AI's generative capabilities to assist people in compensating for their impaired language. Large Language Models (LLMs) have emerged as a recent breakthrough, r...
Early-phase severe complications remain a major cause of morbidity and mortality during induction chemotherapy for acute leukaemia. Existing risk scores capture only limited prognostic variance and are rarely well-calibrated for clinical decision sup...
Perioperative stroke significantly impacts postoperative outcomes. Current risk stratification methods for perioperative stroke prediction lack accuracy and practicality. We aimed to develop a machine learning (ML) model that improves both accuracy a...
Deep learning tools based on computer vision have emerged as alternative methods for assessing radiographic image patterns. These approaches have been explored for various forensic applications, including sex and age estimation. This study aimed to e...
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