Artificial Intelligence Medical Compendium

Nuclei segmentation and classification play a crucial role in the quantitative analysis of computational pathology (CPath). However, the challenge of creating a large volume of labeled pathology nuclei images due to annotation costs has significantly... read more 

This article delves into the application of a neural network (NN) to solve the time fractional diffusion-wave equation (TFDWE), wherein the fractional term is expressed in the Caputo sense of order α with 1 < α < 2. A numerical scheme of order O(t3-α... read more 

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 

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 

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 

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 

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 

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 

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 

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