ReviewToxicology research2018
Big-data and machine learning to revamp computational toxicology and its use in risk assessment.
Review in Toxicology research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed.
- LMF-CP: An Interpretable Multimodal Late-Fusion Framework for Compound Carcinogenicity Prediction.International journal of molecular sciences · 2026Article
- Rewriting paracelsus: linking chemical assessment to public health.Frontiers in toxicology · 2026Review
- Big data and AI: Potential and challenges for digital transformation in toxicology.Environmental analysis, health and toxicology · 2025Article
- MONSTROUS: a web-based chemical-transporter interaction profiler.Frontiers in pharmacology · 2025Article
- Overview of Computational Toxicology Methods Applied in Drug and Green Chemical Discovery.Journal of xenobiotics · 2024Review
- FAIR assessment of nanosafety data reusability with community standards.Scientific data · 2024Article
- Big Question to Developing Solutions: A Decade of Progress in the Development of Aquatic New Approach Methodologies from 2012 to 2022.Environmental toxicology and chemistry · 2024Article
- Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine).Archives of toxicology · 2024Review
- Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling.Toxicological sciences : an official journal of the Society of Toxicology · 2023Article
- Automating Predictive Toxicology Using ComptoxAI.Chemical research in toxicology · 2022Article
- Replacement of animal testing by integrated approaches to testing and assessment (IATA): a call for in vivitrosi.Archives of toxicology · 2022Review
- Developments in high-resolution mass spectrometric analyses of new psychoactive substances.Archives of toxicology · 2022Review
- A framework for chemical safety assessment incorporating new approach methodologies within REACH.Archives of toxicology · 2022Article
- Review
- Revealing Adverse Outcome Pathways from Public High-Throughput Screening Data to Evaluate New Toxicants by a Knowledge-Based Deep Neural Network Approach.Environmental science & technology · 2021Article
- Curated Data In - TrustworthyAlternatives to laboratory animals : ATLA · 2021Review
- Flame: an open source framework for model development, hosting, and usage in production environments.Journal of cheminformatics · 2021Article
- Evaluation of the global performance of eight in silico skin sensitization models using human data.ALTEX · 2021Article
- Bringing Big Data to Bear in Environmental Public Health: Challenges and Recommendations.Frontiers in artificial intelligence · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The creation of large toxicological databases and advances in machine-learning techniques have empowered computational approaches in toxicology. Work with these large databases based on regulatory data has allowed reproducibility assessment of animal models, which highlight weaknesses in traditional
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.