AI Learns Best When Maximising Data Diversity, New Theory Confirms
Researchers have increasingly applied von Neumann entropy (VNE) as a spectral measure of diversity within machine learning, yet a robust...
data
An adaptive, continuous-learning framework for clinical decision-making from proteome-wide biofluid data
The ADAPT-MS frameworkCurrent clinical proteomics pipelines rely on a rigid multi-step process: biomarker discovery is performed in a case–control cohort,...
Hybrid deep learning framework MedFusionNet assists multilabel biomedical risk stratification from imaging and tabular data
The proposed frameworkThe proposed framework integrates multiple components to improve multilabel medical image classification and clinical decision making. It begins...
Explainable machine learning-based classification of traditional Korean ceramics using XRF chemical composition data
Classification accuracy of machine learning modelsA comparative evaluation of the six ML models revealed that both RF and XGB achieved...
Study abroad delivers measurable career impact, data finds
The study found that education abroad is an increasingly powerful signal in the US labour market, with the net impact of study abroad...
Balanced Few-Shot Learning Accurately Diagnoses Retinal Disease With Limited Data, Addressing Imbalance In 1,000 Test Images
Automated diagnosis of retinal diseases, such as diabetic retinopathy and macular degeneration, is increasingly important given their rising prevalence, yet...
