Research graph
References from AI-based nanotoxicity data extraction and prediction of nanotoxicity. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1021/acs.chemrev.3c00070
10.1021/acs.chemrev.3c00070 · External reference
10.1039/c4nr06670g
10.1039/c4nr06670g · External reference
10.1016/j.csbj.2024.03.020
10.1016/j.csbj.2024.03.020 · External reference
10.1016/j.matdes.2023.112452
10.1016/j.matdes.2023.112452 · External reference
Quantitative structure-activity relationship models for predicting inflammatory potential of metal oxide nanoparticles
10.1289/ehp6508 · 2020 · External reference
QSAR modeling of the toxicity classification of superparamagnetic iron oxide nanoparticles (SPIONs) in stem-cell monitoring applications: an integrated study from data curation to model development
10.1039/c9ra09475j · 2020 · External reference
NanoTox: development of a parsimonious in silico model for toxicity assessment of metal-oxide nanoparticles using physicochemical features
10.1021/acsomega.1c01076 · 2021 · External reference
10.1039/c8ra10226k
10.1039/c8ra10226k · External reference
A Nano-QSTR model to predict nano-cytotoxicity: an approach using human lung cells data
10.1186/s12989-023-00530-0 · 2023 · External reference
Review of the effects of manufactured nanoparticles on mammalian target organs
10.1002/jat.3499 · 2018 · External reference
Ecotoxicological effects of carbon based nanomaterials in aquatic organisms
2018 · External reference
Ongoing inflammation enhances the toxicity of engineered nanomaterials: Application of an in vitro co-culture model of the healthy and inflamed intestine
10.1016/j.tiv.2019.104738 · 2020 · External reference
Characterization of oxidative damage induced by nanoparticles via mechanism-driven machine learning approaches
10.1016/j.scitotenv.2023.162103 · 2023 · External reference
Machine learning-enabled nanosafety assessment of multi-metallic alloy nanoparticles modified TiO2 system
10.1016/j.impact.2022.100442 · 2022 · External reference
Prediction of Dynamic Toxicity of Nanoparticles Using Machine Learning
10.3390/toxics12100750 · 2024 · External reference
A systematic quality evaluation and review of nanomaterial genotoxicity studies: a regulatory perspective
10.1186/s12989-022-00499-2 · 2022 · External reference
Toward the development of “nano-QSARs”: advances and challenges
10.1002/smll.200900179 · 2009 · External reference
Novel approach for efficient predictions properties of large pool of nanomaterials based on limited set of species: nano-read-across
10.1088/0957-4484/26/1/015701 · 2015 · External reference
Toxicity Classification of Oxide Nanomaterials: Effects of Data Gap Filling and PChem Score-based Screening Approaches
10.1038/s41598-018-21431-9 · 2018 · External reference
Curation of datasets, assessment of their quality and completeness, and nanoSAR classification model development for metallic nanoparticles
10.1039/c8en00061a · 2018 · External reference
Towards a generalized toxicity prediction model for oxide nanomaterials using integrated data from different sources
10.1038/s41598-018-24483-z · 2018 · External reference
10.1016/j.csbj.2024.02.003 · Admitted local publication
Developing prompts from large language model for extracting clinical information from pathology and ultrasound reports in breast cancer
10.3857/roj.2023.00633 · 2023 · External reference
Data Extraction from Free-Text Reports on Mechanical Thrombectomy in Acute Ischemic Stroke Using ChatGPT: A Retrospective Analysis
10.1148/radiol.232741 · 2024 · External reference
A critical assessment of using ChatGPT for extracting structured data from clinical notes
10.1038/s41746-024-01079-8 · 2024 · External reference
Creating Large Language Model Applications Utilizing LangChain: A Primer on Developing LLM Apps Fast
2023 · External reference
Unresolved reference
2024 · External reference
10.1613/jair.953
10.1613/jair.953 · External reference
Unresolved reference
2024 · External reference
10.1021/jacs.3c05819
10.1021/jacs.3c05819 · External reference
Extracting Accurate Materials Data from Research Papers with Conversational Language Models and Prompt Engineering
10.1038/s41467-024-45914-8 · 2024 · External reference
10.1021/nn3010087
10.1021/nn3010087 · External reference
Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: hints from nano-QSAR studies
10.3109/17435390.2014.930195 · 2015 · External reference
10.1039/c3nr01533e
10.1039/c3nr01533e · External reference
10.1787/9789264085442-en
10.1787/9789264085442-en · External reference
Retrieval-Augmented
2023 · External reference
Distributed Representations of Sentences and Documents
2014 · External reference
Unresolved reference
2013 · External reference
Unresolved reference
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Unresolved reference
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Unresolved reference
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Unresolved reference
External reference
Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52
10.1177/026119290503300209 · 2005 · External reference
Practices and Trends of Machine Learning Application in Nanotoxicology
10.3390/nano10010116 · 2020 · External reference
Application of Machine Learning in Nanotoxicology: A Critical Review and Perspective
10.1021/acs.est.4c03328 · 2024 · External reference
