Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 36,691 to 36,700 of 223,137 articles

Unveiling Fine-Grained Deceptive Patterns in Multimodal Fake News: An Explainable Neuro-Symbolic Framework With LVLMs.

IEEE transactions on pattern analysis and machine intelligence
The widespread proliferation of fake news on the Internet, especially in multi-modal formats, poses a substantial threat to society. Most deep learning-based approaches for fake news detection yield accurate predictions but lack explainability. Exist... read more 

A Unified Experience Replay Framework for Spiking Deep Reinforcement Learning.

IEEE transactions on pattern analysis and machine intelligence
Deep Reinforcement Learning (DRL) methods have shown remarkable success in many applications, yet their high energy consumption limits their practicability. Recent studies incorporated energy-efficient Spiking Neural Networks (SNNs) to build Spiking ... read more 

Reinforcement Learning-Based Sequential Parameter Tuning for Image Signal Processing.

IEEE transactions on pattern analysis and machine intelligence
Hardware image signal processing (ISP) transforms RAW inputs into high-quality RGB images through a series of processing modules, each with numerous tunable parameters. Traditionally, these parameters are manually tuned by imaging experts, a time-con... read more 

Generative AI Empower Addiction-Related Brain Circuits Detection via Graph Diffusion-Infused Adversarial Learning.

IEEE transactions on cybernetics
The study of the nicotine addiction mechanism is of great significance in both nicotine withdrawal and brain science. The detection of addiction-related brain circuitry using functional magnetic resonance imaging (fMRI) is a critical step in studying... read more 

Generative AI-Driven Ergonomics: A Virtual-Real Hybrid Experiment for Human Factors Engineering.

IEEE transactions on cybernetics
Ergonomics or human factors engineering (HFE) mainly exploits human experiments to discover one's cognitive and behavioral mechanisms. Such a paradigm, however, suffers from the scale of subject group and the extent to which they can stand for the wh... read more 

Self-Triggered Prescribed-Time Impulsive Control for Nonlinear Systems.

IEEE transactions on cybernetics
This article presents a new design of self-triggered impulsive control (STIC) for prescribed-time stability (PTS) of nonlinear systems. A prescribed-time convergent function is proposed to determine the impulsive control strength together with the in... read more 

C2-LSM: A Storm-NoC Based Neuromorphic Processor for High-Accuracy Liquid State Machine With Cube-Cluster Topology.

IEEE transactions on biomedical circuits and systems
The liquid state machine (LSM), a reservoir computing variant of spiking neural networks (SNNs), has been widely adopted for its low training complexity. In this work, we propose C2-LSM, a neuromorphic processor designed through algorithm-hardware co... read more 

Bulk Microarray and Single-Cell Transcriptomic Analyses Reveal Bacterial Lipopolysaccharide-Related Biomarkers in Sepsis.

Drug development research
Sepsis, a life-threatening condition triggered by dysregulated host response to infection, poses significant global health challenges. Identifying lipopolysaccharide (LPS)-related biomarkers and underlying mechanisms remains critical, yet underexplor... read more 

Artificial Intelligence in Drug Discovery: Integrative Advances From Data to Therapeutic Innovation.

Drug development research
Integrating artificial intelligence (AI) into drug discovery revolutionizes pharmaceutical research by significantly accelerating the identification, optimization, and development of novel therapeutics. Conventional drug discovery methods, known for ... read more 

Optimized Seizure Detection in EEG Using Dual-Branch Feature Fusion and Machine Learning Technique.

Developmental neurobiology
Epilepsy is a neurological disorder of the brain that generates seizures due to abnormal electrical activity. The diagnosis and management of the disease primarily depend on recordings of the EEG. A multistage methodology for seizure detection with e... read more