Latest AI and machine learning research in surveys for healthcare professionals.
Data heterogeneity plays a pivotal role in determining the performance of machine learning (ML) sy...
Current AIGC detectors often achieve near-perfect accuracy on images produced by the same generato...
Speech Emotion Recognition (SER) is a rapidly evolving field of research that aims to identify and c...
Implicit motives, nonconscious needs that influence individuals' behaviors and shape their emotions,...
The integration of artificial intelligence in nursing practice presents significant ethical challeng...
Coughing behavior is associated with conditions such as sleep apnea, asthma, and chronic obstructive...
The integration of chatbots into psychiatry introduces a novel approach to support clinical decision...
OBJECTIVES: This work evaluated algorithmic bias in biomarkers classification using electronic patho...
Chain-of-thought (CoT) reasoning enhances performance of large language models, but questions rema...
In medical image segmentation, limited external validity remains a critical obstacle when models a...
The present study performs a comprehensive fairness analysis of machine learning (ML) models for t...
Large language models (LLMs) are widely used for long-form text generation. However, factual error...
While bias in large language models (LLMs) is well-studied, similar concerns in vision-language mo...
Mixed methods research integrates quantitative and qualitative data but faces challenges in aligni...
In cloud-scale systems, failures are the norm. A distributed computing cluster exhibits hundreds o...
Artificial Knowledge (AK) systems are transforming decision-making across critical domains such as...
Large language model (LLM)-driven multi-agent systems (MAS) are transforming how humans and AIs co...
Large Vision Language Models (LVLMs) have achieved remarkable progress in multimodal tasks, yet th...
Bio-inspired algorithms (BIAs) utilize natural processes such as evolution, swarm behavior, foragi...
Video-based person re-identification (Re-ID) remains brittle in real-world deployments despite imp...
We introduce Deep Spectral Prior (DSP), a new formulation of Deep Image Prior (DIP) that redefines...