ReviewExperimental biology and medicine (Maywood, N.J.)2023
Review of machine learning and deep learning models for toxicity prediction.
Review in Experimental biology and medicine (Maywood, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 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
51 citing papers in PubMed.
- Artificial intelligence-guided nanozyme engineering for chronic wound healing: from rational design to precision therapeutics.Bioactive materials · 2027Review
- Artificial intelligence in toxicology: current advances, challenges and future directions.Archives of toxicology · 2026Review
- ToxiVerse: chemical bioprofiling, toxicity data sharing and customizable predictive modeling.Bioinformatics (Oxford, England) · 2026Article
- A review of machine learning in toxicology: current practices and reporting gaps.Archives of toxicology · 2026Review
- AI/ML-based computational models for toxicity prediction.Environmental science and pollution research international · 2026Review
- Article
- Advancing the Discovery of Emerging Contaminants: A Leap in Technology and Data.Environmental science & technology · 2026Review
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Article
- Integrating Multiview Information for Enhanced Deep Learning-Based Acute Dermal Toxicity Prediction.Journal of chemical information and modeling · 2026Article
- ToxiVerse: A Public Platform for Chemical Toxicity Data Sharing and Customizable Predictive Modeling.bioRxiv : the preprint server for biology · 2026Article
- Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.Advanced drug delivery reviews · 2026Review
- An ensemble machine learning model based on magnetic resonance imaging features for diagnosing deep infiltrating endometriosis.Frontiers in physiology · 2026Article
- Integrating Microarray Analysis, Machine Learning, and Molecular Docking to Explore the Mechanism of Doxorubicin-induced Cardiotoxicity.Current medicinal chemistry · 2026Article
- Article
- A Metabolism-Informed Neural Network Identifies Pathways Influencing the Potency and Toxicity of Antimicrobial Combinations.npj drug discovery · 2026Article
- Review
- Advances and Challenges in Drug Screening for Cancer Therapy: A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2025Review
- Data augmentation alters feature importance in XGBoost for CVD prediction.Scientific reports · 2025Article
- Construction and effectiveness test of multimodal data fusion prediction model for intracranial infection after severe craniocerebral injury in children based on deep learning.BMC neurology · 2025Article
Corrections and comments
- Commented on by
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ever-increasing number of chemicals has raised public concerns due to their adverse effects on human health and the environment. To protect public health and the environment, it is critical to assess the toxicity of these chemicals. Traditional
Indexed as
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.