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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:

Machine learning in prediction of intrinsic aqueous solubility of drug‐like compounds: Generalization, complexity, or predictive ability?
Mario Lovrić, Kristina Pavlović, Petar Žuvela, et al.
Journal of Chemometrics (2021) Vol. 35, Iss. 7-8
Open Access | Times Cited: 51

Showing 26-50 of 51 citing articles:

Prediction models with multiple machine learning algorithms for POPs: The calculation of PDMS-air partition coefficient from molecular descriptor
Tengyi Zhu, Cuicui Tao
Journal of Hazardous Materials (2021) Vol. 423, pp. 127037-127037
Closed Access | Times Cited: 19
Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances
Mare Oja, Sulev Sild, Geven Piir, et al.
Pharmaceutics (2022) Vol. 14, Iss. 10, pp. 2248-2248
Open Access | Times Cited: 12
Leveraging genetic algorithms to maximise the predictive capabilities of the SOAP descriptor
Trent Barnard, Steven Tseng, James P. Darby, et al.
Molecular Systems Design & Engineering (2022) Vol. 8, Iss. 3, pp. 300-315
Open Access | Times Cited: 10
Designing solvent systems using self-evolving solubility databases and graph neural networks
Yeonjoon Kim, Hojin Jung, Sabari Kumar, et al.
Chemical Science (2023) Vol. 15, Iss. 3, pp. 923-939
Open Access | Times Cited: 5
Application of artificial intelligence in pharmaceutical development
Elena A. Mourelatou, Elias Iosif, Eleftheria Galatou, et al.
Elsevier eBooks (2024), pp. 415-451
Closed Access | Times Cited: 1
Evaluation of Machine Learning Models for Aqueous Solubility Prediction in Drug Discovery
Nian Xue, Yuzhu Zhang, Sensen Liu
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Towards the prediction of drug solubility in binary solvent mixtures at various temperatures using machine learning
Zeqing Bao, Gary Tom, Austin Cheng, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 1
Research and performance analysis of random forest-based feature selection algorithm in sports effectiveness evaluation
Yujiao Li, Yi Mu
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Solubility of Sulfamethazine in the Binary Mixture of Acetonitrile + Methanol from 278.15 to 318.15 K: Measurement, Dissolution Thermodynamics, Preferential Solvation, and Correlation
Claudia Patricia Ortíz, Rossember Edén Cárdenas-Torres, Fleming Martínez, et al.
Molecules (2021) Vol. 26, Iss. 24, pp. 7588-7588
Open Access | Times Cited: 12
PyChemFlow: an automated pre-processing pipeline in Python for reproducible machine learning on chemical data
Mario Lovrić, Tomislav Đuričić, Hussain Hussain, et al.
(2023)
Open Access | Times Cited: 4
Parasitic resistance as a predictor of faulty anodes in electro galvanizing: a comparison of machine learning, physical and hybrid models
Mario Lovrić, Р.А. Мейстер, Thomas Steck, et al.
Advanced Modeling and Simulation in Engineering Sciences (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 9
Utilizing public and private sector data to build better machine learning models for the prediction of pharmacokinetic parameters
Masataka Kuroda, Reiko Watanabe, Tsuyoshi Esaki, et al.
Drug Discovery Today (2022) Vol. 27, Iss. 11, pp. 103339-103339
Open Access | Times Cited: 5
Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children
Ivana Banić, Mario Lovrić, Gerald Cuder, et al.
Asthma Research and Practice (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 6
Towards the Prediction of Drug Solubility in Binary Solvent Mixtures at Various Temperatures Using Machine Learning
Zeqing Bao, Gary Tom, Austin Cheng, et al.
Research Square (Research Square) (2024)
Open Access
Merging Counter-Propagation and Back-Propagation Algorithms: Overcoming the Limitations of Counter-Propagation Neural Network Models
Viktor Drgan, Katja Venko, Janja Sluga, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 8, pp. 4156-4156
Open Access
A Chemical Structure and Machine Learning Approach to Assess the Potential Bioactivity of Endogenous Metabolites and Their Association with Early Childhood Systemic Inflammation
Mario Lovrić, Tingting Wang, Mads Rønnow Staffe, et al.
Metabolites (2024) Vol. 14, Iss. 5, pp. 278-278
Open Access
A hybrid approach to aqueous solubility prediction using COSMO-RS and machine learning
Niamh Mac Fhionnlaoich, Jacek Żegliński, Melba Simon, et al.
Process Safety and Environmental Protection (2024) Vol. 209, pp. 67-71
Closed Access
Evaluation of Machine Learning Models for Aqueous Solubility Prediction in Drug Discovery
Nian Xue, Yuzhu Zhang, Sensen Liu
(2024), pp. 26-33
Open Access
Machine Learning for the Identification of Key Predictors to Bayley Outcomes: A Preterm Cohort Study
Petra Grđan Stevanović, Nina Barišić, Iva Šunić, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 9, pp. 922-922
Open Access
WaSPred: A reliable AI-based water solubility predictor for small molecules
Miriana Di Stefano, Salvatore Galati, Chiara Lonzi, et al.
International Journal of Pharmaceutics (2024) Vol. 666, pp. 124817-124817
Closed Access
GGAS2SN: Gated Graph and SmilesToSeq Network for Solubility Prediction
Waqar Ahmad, Kil To Chong, Hilal Tayara
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 20, pp. 7833-7843
Closed Access
Machine Learning for Solubility Prediction
Tianyuan Zheng, John B. O. Mitchell, Simon Dobson
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
A chemical structure and machine learning approach to assess the potential bioactivity of endogenous metabolites and their association with early-childhood hs-CRP levels
Mario Lovrić, Tingting Wang, Mads Rønnow Staffe, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
Insignificant Changes in Particulate Matter during the COVID-19 Lockdown: A Machine Learning Study in Zagreb, Croatia
Mario Lovrić, Mario Antunović, Iva Šunić, et al.
Proceedings of the World Congress on Civil, Structural, and Environmental Engineering (2022)
Open Access
Nanodrug delivery systems in cancer therapy
Andrew G. Mtewa, Jonathan T. Bvunzawabaya, Fanuel Lampiao
Elsevier eBooks (2022), pp. 239-254
Closed Access

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