AI Medical Compendium Journal:
Toxicology

Showing 11 to 18 of 18 articles

Deep Learning Algorithm Based on Molecular Fingerprint for Prediction of Drug-Induced Liver Injury.

Toxicology
Drug-induced liver injury (DILI) is one the rare adverse drug reaction (ADR) and multifactorial endpoints. Current preclinical animal models struggle to anticipate it, and in silico methods have emerged as a way with significant potential for doing s...

A deep-learning approach for identifying prospective chemical hazards.

Toxicology
With the aim of helping to set safe exposure limits for the general population, various techniques have been implemented to conduct risk assessments for chemicals and other environmental stressors; however, none of these tools facilitate the identifi...

Toxicity prediction of nanoparticles using machine learning approaches.

Toxicology
Nanoparticle toxicity analysis is critical for evaluating the safety of nanomaterials due to their potential harm to the biological system. However, traditional experimental methods for evaluating nanoparticle toxicity are expensive and time-consumin...

TSSF-hERG: A machine-learning-based hERG potassium channel-specific scoring function for chemical cardiotoxicity prediction.

Toxicology
The human ether-à-go-go-related gene (hERG) encodes the Kv11.1 voltage-gated potassium ion (K) channel that conducts the rapidly activating delayed rectifier current (I) in cardiomyocytes to regulate the repolarization process. Some drugs, as blocker...

Derivation, characterisation and analysis of an adverse outcome pathway network for human hepatotoxicity.

Toxicology
Adverse outcome pathways (AOPs) and their networks are important tools for the development of mechanistically based non-animal testing approaches, such as in vitro and/or in silico assays, to assess toxicity induced by chemicals. In the present study...

Safer chemicals using less animals: kick-off of the European ONTOX project.

Toxicology
The 3Rs concept, calling for replacement, reduction and refinement of animal experimentation, is receiving increasing attention around the world, and has found its way to legislation, in particular in the European Union. This is aligned by continuing...

Ontology-based semantic mapping of chemical toxicities.

Toxicology
This study was undertaken to evaluate the use of ontology-based semantic mapping (OS-Mapping) in chemical toxicity assessment. Nineteen chemical-species phenotypic profiles (CSPPs) were constructed by ontologically annotating the toxicity responses r...

A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds.

Toxicology
Cancer is one of the main causes of death in Western countries, and a major issue for human health. Prolonged exposure to a number of chemicals was observed to be one of the primary causes of cancer in occupationally exposed persons. Thus, the develo...