AI Medical Compendium Topic

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

Lipids

Showing 61 to 70 of 124 articles

Clear Filters

An Approach to Biomarker Discovery of Cannabis Use Utilizing Proteomic, Metabolomic, and Lipidomic Analyses.

Cannabis and cannabinoid research
Relatively little is known about the molecular pathways influenced by cannabis use in humans. We used a multi-omics approach to examine protein, metabolomic, and lipid markers in plasma differentiating between cannabis users and nonusers to understa...

Using isotopic envelopes and neural decision tree-based in silico fractionation for biomolecule classification.

Analytica chimica acta
Untargeted mass spectrometry (MS) workflows are more suitable than targeted workflows for high throughput characterization of complex biological samples. However, analysis workflows for untargeted methods are inadequate for characterization of comple...

Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue Virus-Infected Cells.

Molecules (Basel, Switzerland)
Drug target prediction is an important method for drug discovery and design, can disclose the potential inhibitory effect of active compounds, and is particularly relevant to many diseases that have the potential to kill, such as dengue, but lack any...

A machine learning approach to estimation of phase diagrams for three-component lipid mixtures.

Biochimica et biophysica acta. Biomembranes
The plasma membrane of eukaryotic cells is commonly believed to contain ordered lipid domains. The interest in understanding the origin of such domains has led to extensive studies on the phase behavior of mixed lipid systems. Three-component phase d...

Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data.

Computational and mathematical methods in medicine
The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic ...

Deep-learning models for lipid nanoparticle-based drug delivery.

Nanomedicine (London, England)
Early prediction of time-lapse microscopy experiments enables intelligent data management and decision-making. Using time-lapse data of HepG2 cells exposed to lipid nanoparticles loaded with mRNA for expression of GFP, the authors hypothesized that...

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.

BMC endocrine disorders
INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and v...

Classification and Identification of Archaea Using Single-Cell Raman Ejection and Artificial Intelligence: Implications for Investigating Uncultivated Microorganisms.

Analytical chemistry
Archaea can produce special cellular components such as polyhydroxyalkanoates, carotenoids, rhodopsin, and ether lipids, which have valuable applications in medicine and green energy production. Most of the archaeal species are uncultivated, posing c...

Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

Proceedings of the National Academy of Sciences of the United States of America
RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-at...