Artificial Intelligence Medical Compendium

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

Showing 27,731 to 27,740 of 218,939 articles

Integration of AHRR methylation, heavy metals, and clinical characteristics for urothelial carcinoma risk stratification: An explainable artificial intelligence approach.

Environmental pollution (Barking, Essex : 1987)
The short metabolic half-life of conventional tobacco biomarkers often limits their ability to reflect cumulative toxicological damage, which may complicate risk stratification for urothelial carcinoma (UC). This study explored an explainable artific... read more 

Screening of metabolic-related biomarkers linking intervertebral disc degeneration and type 2 diabetes based on comprehensive bioinformatics analysis and machine learning.

Biochemistry and biophysics reports
BACKGROUND: Intervertebral disc degeneration (IVDD) is a prominent etiology of lower back pain. Type 2 diabetes (T2D), the most prevalent metabolic disorder, may expedite IVDD progression through mechanisms involving hyperglycemia, advanced glycation... read more 

Robust validation of neuroimaging and clinical models via the SAR method: A case study based on the ADNI dataset.

NeuroImage
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and substantial brain atrophy. Early and accurate prediction of disease progression and staging is crucial for timely intervention and effective t... read more 

Pilot evaluation of a large language model-mediated pre-consultation interview for vestibular disorders.

Auris, nasus, larynx
OBJECTIVE: Efficient and high-quality history taking is central to vestibular diagnosis, but it is often constrained by limited consultation time and variable patient understanding of questionnaires. Large language models (LLMs) can help structure in... read more 

Artificial intelligence-assisted design and optimization of stimuli-responsive nanocarriers for smart drug delivery.

Materials today. Bio
Stimuli-responsive nanostructures are a revolutionary breakthrough in the controlled delivery of drugs, allowing for their precise spatiotemporal control. These intelligent materials are designed to respond to internal stimuli (such as pH, redox grad... read more 

Precision nutrition in breast cancer: Towards patient- and tumour-informed dietary strategies.

Clinical nutrition (Edinburgh, Scotland)
Dietary strategies are increasingly recognized as important modulators of breast cancer outcomes, acting through effects on metabolic regulation, weight management, hormone signalling, immune function, and the gut microbiome. However, breast cancer h... read more 

A 48-class handwritten dataset for the endangered chakma language.

Data in brief
This article describes a comprehensive handwritten character dataset for the endangered Chakma language, primarily spoken in the Chittagong Hill Tracts of Bangladesh. The dataset comprises 37,708 processed RGB images, standardized to 40 × 40 pixels, ... read more 

Accuracy of machine learning models for mitral regurgitation severity assessment: A systematic review and meta-analysis.

International journal of cardiology. Cardiovascular risk and prevention
BACKGROUND: Accurate assessment of mitral regurgitation (MR) severity is crucial for guiding clinical management, but is often limited by the subjectivity and variability of traditional echocardiographic evaluations. Machine learning (ML) models offe... read more 

FishNet: A dataset of freshwater fish from Bangladesh for deep learning-based fish species classification.

Data in brief
The fisheries sector plays a vital role in the economy and food security of Bangladesh. Bangladesh is one of the leading countries in inland fish production. Bangladesh gains sustainable economic benefits from aquaculture and fisheries. This sector m... read more 

Monitoring airline pilot mental health: a 3PM framework utilising digital phenotyping and AI.

The EPMA journal
The aeromedical certification of commercial airline pilots relies on periodic, self-disclosure-dependent assessments. However, this reactive model lacks the temporal resolution required to capture the gradual behavioural and physiological perturbatio... read more