ReviewACS polymers Au2023
A User's Guide to Machine Learning for Polymeric Biomaterials.
Review in ACS polymers Au, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed, 81 citations in OpenAlex.
- Engineering Oxidative Stress for Precision Therapy: Reactive Oxygen Species-Responsive Hydrogel-Nanocarrier Systems as Translational Redox Drug-Delivery Platforms.ACS pharmacology & translational science · 2026Review
- Soft Computing Approaches toward Density-Based Analysis of Many-Electron Systems.ACS physical chemistry Au · 2026Review
- Soft, Reactive, and Alive: A Dynamic Framework for Degradation and Functional Stability of Polymeric Biomaterials.Polymers · 2026Review
- Oxygen-Tolerant Photo-Induced Miniaturized Accelerated Atom Transfer Radical Polymerization (OPTIMA-ATRP) for High-Throughput Synthesis of Polymer Bioconjugates.Angewandte Chemie (International ed. in English) · 2026Article
- Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning.Biomacromolecules · 2026Review
- Automated and High-Throughput Phase Separation Control for Supramolecular Polymer Blends Enabled by Machine Learning.JACS Au · 2026Article
- Self-driving lab for the data-driven design of single-chain polymer nanoparticles.Cell press blue · 2026Article
- Predicting early and complete drug release from long-acting injectables using explainable machine learning.International journal of pharmaceutics · 2026Article
- Predictive Modelling of Solvent Effects on Drug Incorporation into Polymeric Nanocarriers: A Machine Learning Approach.Macromolecular rapid communications · 2026Article
- Artificial intelligence-assisted design and optimization of stimuli-responsive nanocarriers for smart drug delivery.Materials today. Bio · 2026Review
- A user's guide to your first self-driving liquid handling lab.Digital discovery · 2026Article
- Interpretable Two-Stage Machine Learning for Early and Full Drug Release Prediction in PLGA Microspheres.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Identifying Polymers that Bind or Reject Proteins with Machine Learning: Handling Categorical Features within a GPR Model.ACS polymers Au · 2026Article
- Data-driven multiscale design of composite biomaterials: Integrating experiments, imaging, and computational modeling for biomedical engineering.Materials today. Bio · 2026Review
- Automation-Assisted Photoinduced Atom Transfer Radical Polymerization.ACS polymers Au · 2026Article
- Machine learning for extracellular vesicles enables diagnostic and therapeutic nanobiotechnology.Journal of nanobiotechnology · 2026Review
- Predicting Early and Complete Drug Release from Long-Acting Injectables Using Explainable Machine Learning.ArXiv · 2026Article
- Theragenerative Nanomaterials: Integrating Therapy, Regeneration, and Diagnosis-Navigating the Shared Pathways Between Tissue Repair and Malignancy.International journal of nanomedicine · 2026Review
- SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles.Biophysical journal · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The development of novel biomaterials is a challenging process, complicated by a design space with high dimensionality. Requirements for performance in the complex biological environment lead to difficult
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.