AI Medical Compendium Topic

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

Datasets as Topic

Showing 191 to 200 of 1079 articles

Clear Filters

A machine learning approach for single cell interphase cell cycle staging.

Scientific reports
The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in...

Artificial intelligence-based detection of epimacular membrane from color fundus photographs.

Scientific reports
Epiretinal membrane (ERM) is a common ophthalmological disorder of high prevalence. Its symptoms include metamorphopsia, blurred vision, and decreased visual acuity. Early diagnosis and timely treatment of ERM is crucial to preventing vision loss. Al...

VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics.

Nature communications
Deep learning architectures such as variational autoencoders have revolutionized the analysis of transcriptomics data. However, the latent space of these variational autoencoders offers little to no interpretability. To provide further biological ins...

A comparative study on image-based snake identification using machine learning.

Scientific reports
Automated snake image identification is important from different points of view, most importantly, snake bite management. Auto-identification of snake images might help the avoidance of venomous snakes and also providing better treatment for patients...

Mapping the glycosyltransferase fold landscape using interpretable deep learning.

Nature communications
Glycosyltransferases (GTs) play fundamental roles in nearly all cellular processes through the biosynthesis of complex carbohydrates and glycosylation of diverse protein and small molecule substrates. The extensive structural and functional diversifi...

A novel lncRNA-protein interaction prediction method based on deep forest with cascade forest structure.

Scientific reports
Long noncoding RNAs (lncRNAs) regulate many biological processes by interacting with corresponding RNA-binding proteins. The identification of lncRNA-protein Interactions (LPIs) is significantly important to well characterize the biological functions...

Predicting medication adherence using ensemble learning and deep learning models with large scale healthcare data.

Scientific reports
Clinical studies from WHO have demonstrated that only 50-70% of patients adhere properly to prescribed drug therapy. Such adherence failure can impact therapeutic efficacy for the patients in question and compromises data quality around the populatio...

Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study.

PloS one
BACKGROUND: Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. Epidemiologists should understand how ML algorithms behave within the context of outbreak data where missingness of data is almost ubiquitous.

Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer's disease neuropathologies.

Nature communications
Deep neural networks (DNNs) capture complex relationships among variables, however, because they require copious samples, their potential has yet to be fully tapped for understanding relationships between gene expression and human phenotypes. Here we...

MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation.

NeuroImage
The annotation of brain lesion images is a key step in clinical diagnosis and treatment of a wide spectrum of brain diseases. In recent years, segmentation methods based on deep learning have gained unprecedented popularity, leveraging a large amount...