Data-driven AI systems increasingly influence our choices, raising concerns about autonomy, fairness, and accountability. Achieving algorithmic autonomy requires new infrastructures, motivation ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

New AI model decodes brain signals captured noninvasively via EEG opens the possibility of developing future neuroprosthetics ...

AI is searching particle colliders for the unexpected ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

The evolution of AI-powered vehicle inspection has moved rapidly from experimental research to an essential pillar of the modern automotive ecosystem. Historically, vehicle checks were manual and ...

Led by Professor Fu Jin, the study addresses a critical challenge in radiation therapy: balancing the computational speed and ...

Abstract: Imbalanced image classification faces critical challenges in balancing the quality and diversity of synthetic minority samples. This article proposes the improved estimation distribution ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...

Trained on data from NASA's exoplanet-hunting missions, the open-source ExoMiner++ deep learning model uses an advanced ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Background and Aims: Obstructive coronary artery disease (CAD) can lead to myocardial infarction or cardiac death. The accuracy of conventional risk prediction models is limited, leading to excessive ...