AI Medical Compendium Topic

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

Cell Line

Showing 21 to 30 of 223 articles

Clear Filters

Evaluation of the cytotoxic effect of titanium dioxide nanoparticles in human embryonic lung cells.

Turkish journal of medical sciences
BACKGROUND/AIM: Titanium dioxide nanoparticles are widely used in a variety of products, including sunscreens, paints, and ceramics. However, their increasing use has raised concerns about their potential health risks. Titanium dioxide nanoparticles ...

Improving drug response prediction via integrating gene relationships with deep learning.

Briefings in bioinformatics
Predicting the drug response of cancer cell lines is crucial for advancing personalized cancer treatment, yet remains challenging due to tumor heterogeneity and individual diversity. In this study, we present a deep learning-based framework named Dee...

Target Cell Extraction and Spectrum-Effect Relationship Coupled with BP Neural Network Classification for Screening Potential Bioactive Components in Ginseng Extract with a Protective Effect against Myocardial Damage.

Molecules (Basel, Switzerland)
Cardiovascular disease has become a common ailment that endangers human health, having garnered widespread attention due to its high prevalence, recurrence rate, and sudden death risk. Ginseng possesses functions such as invigorating vital energy, en...

Exploring machine learning for untargeted metabolomics using molecular fingerprints.

Computer methods and programs in biomedicine
BACKGROUND: Metabolomics, the study of substrates and products of cellular metabolism, offers valuable insights into an organism's state under specific conditions and has the potential to revolutionise preventive healthcare and pharmaceutical researc...

Machine learning-based 3D segmentation of mitochondria in polarized epithelial cells.

Mitochondrion
Mitochondria are dynamic organelles that alter their morphological characteristics in response to functional needs. Therefore, mitochondrial morphology is an important indicator of mitochondrial function and cellular health. Reliable segmentation of ...

Visualization strategies to aid interpretation of high-dimensional genotoxicity data.

Environmental and molecular mutagenesis
This article describes a range of high-dimensional data visualization strategies that we have explored for their ability to complement machine learning algorithm predictions derived from MultiFlow® assay results. For this exercise, we focused on seve...

Predicting Transcription Factor Binding Sites with Deep Learning.

International journal of molecular sciences
Prediction of binding sites for transcription factors is important to understand how the latter regulate gene expression and how this regulation can be modulated for therapeutic purposes. A consistent number of references address this issue with diff...

Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning.

Nature communications
mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking. Here, we design 5'UTRs for efficient mRNA translation using deep learning. We perform polysome...

EPI-Trans: an effective transformer-based deep learning model for enhancer promoter interaction prediction.

BMC bioinformatics
BACKGROUND: Recognition of enhancer-promoter Interactions (EPIs) is crucial for human development. EPIs in the genome play a key role in regulating transcription. However, experimental approaches for classifying EPIs are too expensive in terms of eff...

A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.

Nature communications
Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here we developed an artificial intelligence (AI)-powered automated framework for ready detection of vir...