Artificial Intelligence Medical Compendium

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

Showing 1,831 to 1,840 of 165,003 articles

Classifying social and physical pain from multimodal physiological signals using machine learning.

Scientific reports
Accurate pain assessment is essential for effective management; however, most studies have focused on differentiating pain from non-pain or estimating pain intensity rather than distinguishing between distinct pain types. We present a machine learnin... read more 

Nondestructive freshness recognition of chicken breast meat based on deep learning.

Scientific reports
Identifying chicken breast freshness is an important component of poultry food safety. Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. In this study, th... read more 

Integrated transcriptomic and proteomic analysis identifies FBXW7 as a key regulator of tau homeostasis in Alzheimer's disease.

Journal of Alzheimer's disease : JAD
BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder driven by complex, incompletely understood genetic and pathogenic factors. E3 ubiquitin ligases (E3s), crucial for protein degradation, are implicated in AD, but their spe... read more 

: categorical diffusion ensembles for single-step chemical retrosynthesis.

Journal of cheminformatics
Methods for automatic chemical retrosynthesis have found recent success through the application of models traditionally built for natural language processing, primarily through transformer neural networks. These models have demonstrated significant a... read more 

The mediating effects of technology trust and perceived value in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence in nursing: a cross-sectional study.

BMC nursing
BACKGROUND: Attitude toward the usage of artificial intelligence in nursing directly affect nurses' technology adoption behavior. Positive attitude toward the usage of artificial intelligence can help nurses analyze large data sets and propose potent... read more 

Multiple Tumor-related autoantibodies test enhances CT-based deep learning performance in diagnosing lung cancer with diameters < 70 mm: a prospective study in China.

BMC pulmonary medicine
BACKGROUND: Deep learning (DL) demonstrates high sensitivity but low specificity in lung cancer (LC) detection during CT screening, and the seven Tumor-associated antigens autoantibodies (7-TAAbs), known for its high specificity in LC, was employed t... read more 

A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.

Scientific reports
The accurate prediction of blood glucose is critical for the effective management of diabetes. Modern continuous glucose monitoring (CGM) technology enables real-time acquisition of interstitial glucose concentrations, which can be calibrated against... read more 

Non-invasive breath testing to detect colorectal cancer: protocol for a multicentre, case-control development and validation study (COBRA2 study).

BMC cancer
BACKGROUND: Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom. The five-year survival rate from CRC is only 10% when discovered at a late stage, but can exceed 90% if diagnosed early. Symptoms related to CRC can be non-sp... read more 

A Multi-Model Ensemble for Advanced Prediction of Reverse Osmosis Performance in Full-Scale Zero-Liquid Discharge Systems.

Environmental science & technology
The growing reliance on reverse osmosis (RO) in zero liquid discharge (ZLD) and seawater desalination has underscored membrane fouling as a critical challenge, requiring predictive tools for proactive management. This study proposes a novel multidime... read more 

Drug-target interaction prediction based on graph convolutional autoencoder with dynamic weighting residual GCN.

BMC bioinformatics
BACKGROUND: The exploration of drug-target interactions (DTIs) is a critical step in drug discovery and drug repurposing. Recently, network-based methods have emerged as a prominent research area for predicting DTIs. These methods excel by extracting... read more