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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Artificial Intelligence-Based Toxicity Prediction of Environmental Chemicals: Future Directions for Chemical Management Applications
Jaeseong Jeong, Jinhee Choi
Environmental Science & Technology (2022) Vol. 56, Iss. 12, pp. 7532-7543
Closed Access | Times Cited: 80

Showing 1-25 of 80 citing articles:

Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology
Ajay Vikram Singh, Vaisali Chandrasekar, Namuna Paudel, et al.
Biomedicine & Pharmacotherapy (2023) Vol. 163, pp. 114784-114784
Open Access | Times Cited: 81
Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management
Simona Mariana Popescu, Sheikh Mansoor, Owais Ali Wani, et al.
Frontiers in Environmental Science (2024) Vol. 12
Open Access | Times Cited: 48
Global environmental and toxicological data of emerging plasticizers: current knowledge, regrettable substitution dilemma, green solution and future perspectives
Abdul Qadeer, Muhammad Yunus Anis, Genoa R. Warner, et al.
Green Chemistry (2024) Vol. 26, Iss. 10, pp. 5635-5683
Closed Access | Times Cited: 31
Artificial intelligence (AI)—it’s the end of the tox as we know it (and I feel fine)*
Nicole Kleinstreuer, Thomas Härtung
Archives of Toxicology (2024) Vol. 98, Iss. 3, pp. 735-754
Open Access | Times Cited: 28
Transformers enable accurate prediction of acute and chronic chemical toxicity in aquatic organisms
Mikael Gustavsson, Styrbjörn Käll, Patrik Svedberg, et al.
Science Advances (2024) Vol. 10, Iss. 10
Open Access | Times Cited: 18
TOXRIC: a comprehensive database of toxicological data and benchmarks
Lianlian Wu, Bowei Yan, Junshan Han, et al.
Nucleic Acids Research (2022) Vol. 51, Iss. D1, pp. D1432-D1445
Open Access | Times Cited: 42
Advances and applications of machine learning and deep learning in environmental ecology and health
Shixuan Cui, Yuchen Gao, Yizhou Huang, et al.
Environmental Pollution (2023) Vol. 335, pp. 122358-122358
Closed Access | Times Cited: 31
Artificial intelligence as the new frontier in chemical risk assessment
Thomas Härtung
Frontiers in Artificial Intelligence (2023) Vol. 6
Open Access | Times Cited: 24
A recipe for plastic: Expert insights on plastic additives in the marine environment
Thomas Maes, Fiona Preston-Whyte, Stephanie Lavelle, et al.
Marine Pollution Bulletin (2023) Vol. 196, pp. 115633-115633
Open Access | Times Cited: 23
Systematic computational toxicity analysis of the ozonolytic degraded compounds of azo dyes: Quantitative structure-activity relationship (QSAR) and adverse outcome pathway (AOP) based approach
Venkata Sai Reddy Ramireddy, Rakshitha Kurakula, Padmanaban Velayudhaperumal Chellam, et al.
Environmental Research (2023) Vol. 231, pp. 116142-116142
Closed Access | Times Cited: 22
Quantitative identification of the co-exposure effects of e-waste pollutants on human oxidative stress by explainable machine learning
Luhan Yang, Tao Zhang, Yanxia Gao, et al.
Journal of Hazardous Materials (2024) Vol. 466, pp. 133560-133560
Closed Access | Times Cited: 13
Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions
Lingxuan Meng, Beihai Zhou, Haijun Liu, et al.
The Science of The Total Environment (2024) Vol. 946, pp. 174201-174201
Closed Access | Times Cited: 9
Exploring the use of Artificial Intelligence (AI) for extracting and integrating data obtained through New Approach Methodologies (NAMs) for chemical risk assessment
Tilmann Blümmel, Johannes Rehn, Carla Mereu, et al.
EFSA Supporting Publications (2024) Vol. 21, Iss. 1
Open Access | Times Cited: 8
An updated review of functional ingredients of Manuka honey and their value-added innovations
Sunan Wang, Yi Qiu, Fan Zhu
Food Chemistry (2023) Vol. 440, pp. 138060-138060
Open Access | Times Cited: 17
Read-across-based intelligent learning: development of a global q-RASAR model for the efficient quantitative predictions of skin sensitization potential of diverse organic chemicals
Arkaprava Banerjee, Kunal Roy
Environmental Science Processes & Impacts (2023) Vol. 25, Iss. 10, pp. 1626-1644
Closed Access | Times Cited: 16
AI and ML-based risk assessment of chemicals: predicting carcinogenic risk from chemical-induced genomic instability
Ajay Vikram Singh, Preeti Bhardwaj, Peter Laux, et al.
Frontiers in Toxicology (2024) Vol. 6
Open Access | Times Cited: 7
Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling
Amirreza Daghighi, Gerardo M. Casañola‐Martín, Kweeni Iduoku, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 23, pp. 10116-10127
Closed Access | Times Cited: 6
Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models
Yuanxi Huang, Lingjun Bu, Kuan Huang, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 26, pp. 11504-11513
Closed Access | Times Cited: 6
Amino Acid Transporter as a Potential Carrier Protein for the Root-to-Shoot Translocation of Polybrominated Diphenyl Ethers in Rice
Jie Chen, Wei Wang, Lizhong Zhu
Environmental Science & Technology (2023) Vol. 57, Iss. 26, pp. 9722-9731
Closed Access | Times Cited: 15
Screening androgen receptor agonists of fish species using machine learning and molecular model in NORMAN water-relevant list
Xiao-Bing Long, Chong-Rui Yao, Siying Li, et al.
Journal of Hazardous Materials (2024) Vol. 468, pp. 133844-133844
Closed Access | Times Cited: 5
A deep learning based multi-model approach for predicting drug-like chemical compound’s toxicity
Konda Mani Saravanan, Jiang-Fan Wan, Liujiang Dai, et al.
Methods (2024) Vol. 226, pp. 164-175
Closed Access | Times Cited: 5
Regional disparities in PPCPs contamination of urban wastewater treatment plants: Unveiling influential factors and ecological effects
Xing Chen, Xiaofei Lu, Juin-Wei Peng, et al.
Environmental Pollution (2025) Vol. 367, pp. 125687-125687
Closed Access
Interpretable artificial intelligence for advancing slope stability assessment techniques with Technosols
Jiazhou Li, Mengjie Huang, M Ma, et al.
Soil Use and Management (2025) Vol. 41, Iss. 1
Closed Access
Multi-task multi-view and iterative error-correcting random forest for acute toxicity prediction
Jie Gao, Lianlian Wu, Guangyi Lin, et al.
Expert Systems with Applications (2025), pp. 126972-126972
Closed Access
New trend on chemical structure representation learning in toxicology: In reviews of machine learning model methodology
Jiabin Zhang, Lei Zhao, Wei Wang, et al.
Critical Reviews in Environmental Science and Technology (2025), pp. 1-26
Closed Access
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