Artificial Intelligence Medical Compendium

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

Showing 67,981 to 67,990 of 233,231 articles

Establishing associations of neighborhood built environment with childhood bedtime.

Environmental research
Emerging evidence implicates that built environment is involved in regulating sleep timing. However, few studies have examined multiple exposures, and the combined effects remain unexplored. Based on merging of geospatial imaging with dataset derived... read more 

Neuroanatomical-based machine learning prediction of Alzheimer's Disease across sex and age.

Neuroscience
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. In 2024 it affected approximately 1 in 9 people aged 65 and older in the U.S., 6.9 million individuals. Early detection and accur... read more 

A review of deep learning techniques in Alzheimer's disease with emphasis on data tools and transfer learning.

Neuroscience
Alzheimer's disease (AD) is a significant neurological condition that is marked by the gradual decline of memory and cognitive function, with a higher incidence observed in older individuals. The mental deterioration associated with this condition is... read more 

Machine learning-enhanced electrochemical sensing platform for simultaneous detection of multiple antibiotics in food samples.

Food chemistry
The increasing prevalence of antibiotic residues in food presents a significant threat to global public health. To address this critical concern, we developed a novel artificial neural network (ANN)-enhanced electrochemical sensor based on ZIF-8/MnMo... read more 

TBC-ac4C: Identification of N4-acetylcytidine sites by incorporating TCN and BiGRU based on multi-head cross-attention mechanism.

Computational biology and chemistry
N4-acetylcytidine (ac4C), a pivotal post-transcriptional modification, modulates mRNA lifecycle dynamics and is linked to numerous pathologies. Accurate genome-wide identification of ac4C sites is fundamental to functional characterization, but exist... read more 

PLSTM-MTGF: A deep learning fusion model enabling real-time multi-target monitoring of penicillin fermentation via near-infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Real-time, multi-parameter monitoring is essential for optimizing industrial penicillin fermentation, yet conventional assays are slow and prone to contamination. This study introduces a lightweight dual-stream fusion model-Partial Least Squares Regr... read more 

Optimising Sleep Stage Detection Using a Minimal Non-EEG Physiological Signal Set and Deep Learning.

Journal of sleep research
Automatic sleep stage classification is essential for enabling non-invasive, at-home monitoring. However, current methods often rely on electroencephalogram (EEG) signals and ad-hoc development approaches that limit reproducibility. We present a repr... read more 

Precision dermatology 2050: AI-driven personalized monitoring and individualized treatment.

Journal of the European Academy of Dermatology and Venereology : JEADV
By 2050, advances in artificial intelligence (AI), Internet of Medical Things (IoMT) and teledermatology are predicted to fundamentally transform the diagnosis and management of chronic inflammatory skin conditions. This white paper examines the anti... read more 

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

Clinical and translational radiation oncology
BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for several primary and metastatic malignancies; however, considerable heterogeneity remains in its definition, clinical indications, and technical delivery. M... read more 

Align then clip: Refining graph for face clustering.

Neural networks : the official journal of the International Neural Network Society
Face clustering, a critical task for annotating large-scale unlabeled face recognition datasets, aims to group facial images of the same identity while minimizing annotation costs. Recent approaches model face relationships as graphs and leverage gra... read more