ReviewPolymers2025
Support Vector Machines in Polymer Science: A Review.
Review in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Digital Twin-Driven Optimization of Pilot-Scale Polyurethane Aerogel Production Using SVR Modelling.Gels (Basel, Switzerland) · 2026Article
- Polymer Drug Conjugate: A Revolution in Drug Delivery.AAPS PharmSciTech · 2026Review
- Comparative assessment of machine learning models for polymer solution viscosity prediction in enhanced oil recovery.Scientific reports · 2026Article
- AI-driven nanomedicine for cancer theranostics.Molecular cancer · 2026Review
- Graph Neural Networks for Polymer Characterization and Property Prediction: Opportunities and Challenges.Journal of chemical information and modeling · 2026Review
- Sustainable design of organic solar cells utilized machine and deep learning.Scientific reports · 2026Article
- Modeling and Comparative Study on Cure Kinetics for CFRP: Autocatalytic vs. Neural Network vs. Angle Information-Enhanced RBF Models.Polymers · 2025Article
- Tabular prior-data fitted network in real-world CT radiomics: benignQuantitative imaging in medicine and surgery · 2025Article
- Optimized machine learning based comparative analysis of predictive models for classification of kidney tumors.Scientific reports · 2025Article
- Scientific Machine Learning for Polymeric Materials.Polymers · 2025Article
- Application of multimodal machine learning-based analysis for the biomethane yields of NaOH-pretreated biomass.Scientific reports · 2025Article
- Review
- Predicting Cognitive Decline in Motoric Cognitive Risk Syndrome Using Machine Learning Approaches.Diagnostics (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Polymer science, a discipline focusing on the synthesis, characterization, and application of macromolecules, has increasingly benefited from the adoption of machine learning (ML) techniques. Among these, Support Vector Machines (SVMs) stand out for their ability to handle nonlinear relationships and high-dimensional datasets, which are common in polymer research. This review explores the diverse applications of SVM in polymer science. Key examples include the prediction of mechanical and thermal properties, optimization of polymerization processes, and modeling of degradation mechanisms. The advantages of SVM are contrasted with its challenges, including computational cost, data dependency, and the need for hyperparameter tuning. Future opportunities, such as the development of polymer-specific kernels and integration with real-time manufacturing systems, are also discussed.
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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.