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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:

In Silico Models to Predict the Perturbation of Molecular Initiating Events Related to Thyroid Hormone Homeostasis
Marina García de Lomana, Andreas Georg Weber, Barbara Birk, et al.
Chemical Research in Toxicology (2020) Vol. 34, Iss. 2, pp. 396-411
Open Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Thyroid Disease Prediction Using Selective Features and Machine Learning Techniques
Rajasekhar Chaganti, Furqan Rustam, Isabel de la Torre Díez, et al.
Cancers (2022) Vol. 14, Iss. 16, pp. 3914-3914
Open Access | Times Cited: 74
Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection
M. Latif, Zohaib Mushtaq, Saad Arif, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 78, Iss. 3, pp. 4225-4241
Open Access | Times Cited: 41
Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data
Katarzyna Arturi, Juliane Hollender
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 18067-18079
Open Access | Times Cited: 42
Detecting Thyroid Disease Using Optimized Machine Learning Model Based on Differential Evolution
Punit Gupta, Furqan Rustam, Khadija Kanwal, et al.
International Journal of Computational Intelligence Systems (2024) Vol. 17, Iss. 1
Open 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: 11
Enhanced thyroid disease prediction using ensemble machine learning: a high-accuracy approach with feature selection and class balancing
Md. Rezaul Islam, Aniruddha Islam Chowdhury, Sharmin Shama, et al.
Discover Artificial Intelligence (2025) Vol. 5, Iss. 1
Open Access | Times Cited: 1
Application of ToxCast/Tox21 data for toxicity mechanism-based evaluation and prioritization of environmental chemicals: Perspective and limitations
Jaeseong Jeong, Donghyeon Kim, Jinhee Choi
Toxicology in Vitro (2022) Vol. 84, pp. 105451-105451
Closed Access | Times Cited: 37
Machine learning on thyroid disease: a review
Kwang‐Sig Lee, Hyuntae Park
Frontiers in Bioscience-Landmark (2022) Vol. 27, Iss. 3, pp. 0101-0101
Open Access | Times Cited: 36
Machine Learning Model for Screening Thyroid Stimulating Hormone Receptor Agonists Based on Updated Datasets and Improved Applicability Domain Metrics
Wenjia Liu, Zhongyu Wang, Jingwen Chen, et al.
Chemical Research in Toxicology (2023) Vol. 36, Iss. 6, pp. 947-958
Closed Access | Times Cited: 19
Early Thyroid Risk Prediction by Data Mining and Ensemble Classifiers
Mohammad H. Alshayeji
Machine Learning and Knowledge Extraction (2023) Vol. 5, Iss. 3, pp. 1195-1213
Open Access | Times Cited: 16
SSC: The novel self-stack ensemble model for thyroid disease prediction
Shengkang Ji
PLoS ONE (2024) Vol. 19, Iss. 1, pp. e0295501-e0295501
Open Access | Times Cited: 6
ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted Bioactivities
Marina García de Lomana, Andrea Morger, Ulf Norinder, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 7, pp. 3255-3272
Open Access | Times Cited: 25
Leveraging machine learning in precision medicine to unveil organochlorine pesticides as predictive biomarkers for thyroid dysfunction
Samir Shamma, Mohamed Ali Hussein, Eslam M. El-Nahrery, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Blockchain-Based Healthcare Recommender System Using Deep Learning
J. L. Hamsapriya, Tharanga Shetty, B. Neha, et al.
Blockchain technologies (2025), pp. 87-109
Closed Access
Machine learning-assisted identification of environmental pollutants by liquid chromatography coupled with high-resolution mass spectrometry
Haotian Wang, Laijin Zhong, Wenyuan Su, et al.
TrAC Trends in Analytical Chemistry (2024), pp. 117988-117988
Closed Access | Times Cited: 3
Introduction to Special Issue: Computational Toxicology
Nicole Kleinstreuer, Igor V. Tetko, Weida Tong
Chemical Research in Toxicology (2021) Vol. 34, Iss. 2, pp. 171-175
Open Access | Times Cited: 19
Thyroid endocrine disruption and hepatotoxicity induced by bisphenol AF: Integrated zebrafish embryotoxicity test and deep learning
Pengyu Chen, Ruihan Wang, Geng Chen, et al.
The Science of The Total Environment (2022) Vol. 822, pp. 153639-153639
Closed Access | Times Cited: 14
In Silico Identification of Potential Thyroid Hormone System Disruptors among Chemicals in Human Serum and Chemicals with a High Exposure Index
Elena Dracheva, Ulf Norinder, Patrik Rydén, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 12, pp. 8363-8372
Open Access | Times Cited: 14
Efficient thyroid disorder identification with weighted voting ensemble of super learners by using adaptive synthetic sampling technique
Noor Afshan, Zohaib Mushtaq, Faten S. Alamri, et al.
AIMS Mathematics (2023) Vol. 8, Iss. 10, pp. 24274-24309
Open Access | Times Cited: 8
Towards a science-based testing strategy to identify maternal thyroid hormone imbalance and neurodevelopmental effects in the progeny – Part IV: the ECETOC and CLE Proposal for a Thyroid Function-Related Neurodevelopmental Toxicity Testing and Assessment Scheme (Thyroid-NDT-TAS)
Stephanie Melching‐Kollmuss, K. Bothe, Alex Charlton, et al.
Critical Reviews in Toxicology (2023) Vol. 53, Iss. 6, pp. 339-371
Open Access | Times Cited: 7
Recognizing high-priority disinfection byproducts based on experimental and predicted endocrine disrupting data: Virtual screening and in vitro study
Shuxin Sui, Nan Zhou, Huihui Liu, et al.
Chemosphere (2024) Vol. 358, pp. 142239-142239
Closed Access | Times Cited: 2
Quantitative structure–activity relationships of chemical bioactivity toward proteins associated with molecular initiating events of organ-specific toxicity
Domenico Gadaleta, Marina García de Lomana, Eva Serrano‐Candelas, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 2
Predicting Endocrine Disruption Using Conformal Prediction – A Prioritization Strategy to Identify Hazardous Chemicals with Confidence
Maria Sapounidou, Ulf Norinder, Patrik L. Andersson
Chemical Research in Toxicology (2022) Vol. 36, Iss. 1, pp. 53-65
Open Access | Times Cited: 7
Bioactivity descriptors for in vivo toxicity prediction: now and the future
Palle Steen Helmke, Barbara Füzi, Gerhard F. Ecker
Expert Opinion on Drug Metabolism & Toxicology (2024) Vol. 20, Iss. 7, pp. 541-543
Open Access | Times Cited: 1
In Vitro Screening for ToxCast Chemicals Binding to Thyroxine-Binding Globulin
Stephanie A. Eytcheson, Alexander D. Zosel, Jennifer H. Olker, et al.
Chemical Research in Toxicology (2024) Vol. 37, Iss. 10, pp. 1660-1669
Closed Access | Times Cited: 1
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