Artificial Intelligence Medical Compendium

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

Showing 29,901 to 29,910 of 219,931 articles

Accelerating spiking neural networks with photonic reconfigurable devices.

Nature communications
Spiking neural networks face hardware limitations as conventional architectures exhibit low array utilization, underperforming GPU-driven artificial neural networks in vision tasks. We present a programmable spiking neurocomputing architecture using ... read more 

Oral microbiome signatures predict biological age and host health.

Nature communications
Identifying robust, non-invasive biomarkers of biological age is key to preventive medicine. While gut aging clocks exist, the oral microbiome remains underexplored as a quantitative biomarker. Using oral microbiome data from two NHANES cohorts (N = ... read more 

A channel and spatial attentions mechanisms with CNN for enhanced license plate detection.

Scientific reports
Real-world License plate detections presents notable challenges arising due to some factors such as variable illumination, occlusions, complex backgrounds and plate distortions. Traditional approaches such as edge detection often generate numerous fa... read more 

A hybrid dual-stream CNN framework with dynamic data augmentation and improved Manta Ray Foraging Optimization for robust glaucoma detection.

Scientific reports
A progressive neurological condition, glaucoma is one of the main causes of irreversible blindness in the globe. Early detection is crucial to preventing irreversible vision loss however conventional diagnostic methods are often time-consuming, and h... read more 

Comparing energy consumption and accuracy in text classification inference.

Scientific reports
The increasing deployment of large language models (LLMs) in natural language processing (NLP) tasks raises concerns about energy efficiency and sustainability. While prior research has largely focused on energy consumption during model training, the... read more 

Deep learning based instance segmentation of mandarin fruit slices for precision assessment and morphological quantification.

Scientific reports
Accurate instance segmentation of mandarin fruit slices is essential for quantifying segment morphology and central core structure, which are key traits in cultivar evaluation, fruit quality assessment, and postharvest application. Manual measurement... read more 

N-doped MXenes for tribological applications: A high-throughput DFT dataset.

Scientific data
MXenes have emerged as a prominent class of two-dimensional materials in the field of solid lubrication, and nitrogen doping has recently been identified as an effective strategy for tailoring their properties. Herein, we present a comprehensive data... read more