ArticleJournal of cheminformatics2025
Prediction model for chemical explosion consequences via multimodal feature fusion.
Article in Journal of cheminformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Integrating Molecular Semantics and Three-Dimensional Geometry for Critical Property Prediction: A Multimodal GNN-BERT Framework.Molecules (Basel, Switzerland) · 2026Article
- Predicting fire consequences with the transformer model based on multimodal feature fusion.Journal of cheminformatics · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Chemical explosion accidents represent a significant threat to both human safety and environmental integrity. The accurate prediction of such incidents plays a pivotal role in risk mitigation and safety enhancement within the chemical industry. This study proposes an innovative Bayes-Transformer-SVM model based on multimodal feature fusion, integrating Quantitative Structure-Property Relationship (QSPR) and Quantitative Property-Consequence Relationship (QPCR) principles. The model utilizes molecular descriptors derived from the Simplified Molecular Input Line Entry System (SMILES) and Gaussian16 software, combined with leakage condition parameters, as input features to investigate the quantitative relationship between these factors and explosion consequences. A comprehensive validation and evaluation of the constructed model were performed. Results demonstrate that the optimized Bayes-Transformer-SVM model achieves superior performance, with test set metrics reaching an R
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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.