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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:

Prediction of drug adverse events using deep learning in pharmaceutical discovery
Chun Yen Lee, Yi‐Ping Phoebe Chen
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 1884-1901
Closed Access | Times Cited: 65

Showing 26-50 of 65 citing articles:

Prediction of drug side effects with transductive matrix co-completion
Xujun Liang, Ying Fu, Lingzhi Qu, et al.
Bioinformatics (2023) Vol. 39, Iss. 1
Open Access | Times Cited: 6
Predicting drug adverse effects using a new Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD)
Julia Y.H. Liu, John A. Rudd
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 6
Predictive Analytics for Care and Management of Patients With Acute Diseases: Deep Learning–Based Method to Predict Crucial Complication Phenotypes
Jessica Qiuhua Sheng, Paul Jen‐Hwa Hu, Xiao Liu, et al.
Journal of Medical Internet Research (2020) Vol. 23, Iss. 2, pp. e18372-e18372
Open Access | Times Cited: 16
Adverse Drug Reaction Discovery Using a Tumor-Biomarker Knowledge Graph
Meng Wang, Xinyu Ma, Jingwen Si, et al.
Frontiers in Genetics (2021) Vol. 11
Open Access | Times Cited: 15
Comprehensive Review on Drug-target Interaction Prediction - Latest Developments and Overview
Ali K. Abdul Raheem, Ban N. Dhannoon
Current Drug Discovery Technologies (2023) Vol. 21, Iss. 2
Closed Access | Times Cited: 5
A Data-Driven Medical Decision Framework for Associating Adverse Drug Events with Drug-Drug Interaction Mechanisms
Adeeb Noor
Journal of Healthcare Engineering (2022) Vol. 2022, pp. 1-7
Open Access | Times Cited: 8
Artificial Intelligence and Machine Learning in Drug Discovery
Pranav Shah, Dinesh V. Thakkar, Nikita Panchal, et al.
Advances in healthcare information systems and administration book series (2024), pp. 54-75
Closed Access | Times Cited: 1
TIRPnet: Risk prediction of traditional Chinese medicine ingredients based on a deep neural network
Jianxiang Wei, Jimin Dai, Yue-Hong Sun, et al.
Journal of Ethnopharmacology (2024) Vol. 325, pp. 117860-117860
Closed Access | Times Cited: 1
Exploring the impact of co-exposure timing on drug-drug interactions in signal detection through spontaneous reporting system databases: a scoping review
Marianna Cocco, Carla Carnovale, Emilio Clementi, et al.
Expert Review of Clinical Pharmacology (2024) Vol. 17, Iss. 5-6, pp. 441-453
Closed Access | Times Cited: 1
Artificial Intelligence and Big Data for Pharmacovigilance and Patient Safety
Muhammad Aasim Shamim, Muhammad Aaqib Shamim, Pankaj Arora, et al.
Journal of Medicine Surgery and Public Health (2024), pp. 100139-100139
Open Access | Times Cited: 1
A Molecular Image-Based Novel Quantitative Structure-Activity Relationship Approach, Deepsnap-Deep Learning and Machine Learning
Yasunari Matsuzaka, Yoshihiro Uesawa
Current Issues in Molecular Biology (2020), pp. 455-472
Open Access | Times Cited: 11
Deep Learning Models for Intelligent Healthcare: Implementation and Challenges
Sadaqat Ur Rehman, Shanshan Tu, Zubair Shah, et al.
Lecture notes in computer science (2021), pp. 214-225
Closed Access | Times Cited: 10
ADENet: a novel network-based inference method for prediction of drug adverse events
Zhuohang Yu, Zengrui Wu, Weihua Li, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 2
Closed Access | Times Cited: 10
Investigation of a Data Split Strategy Involving the Time Axis in Adverse Event Prediction Using Machine Learning
Katsuhisa Morita, Tadahaya Mizuno, Hiroyuki Kusuhara
Journal of Chemical Information and Modeling (2022) Vol. 62, Iss. 17, pp. 3982-3992
Open Access | Times Cited: 6
SCAN: A shared causal attention network for adverse drug reactions detection in tweets
Humayun Kayesh, Md. Saiful Islam, Junhu Wang, et al.
Neurocomputing (2022) Vol. 479, pp. 60-74
Open Access | Times Cited: 5
M2GCN: multi-modal graph convolutional network for modeling polypharmacy side effects
Qidong Liu, Enguang Yao, Chaoyue Liu, et al.
Applied Intelligence (2022) Vol. 53, Iss. 6, pp. 6814-6825
Closed Access | Times Cited: 5
Develop an ADR prediction system of Chinese herbal injections containing Panax notoginseng saponin: a nested case–control study using machine learning
Xingwei Wu, Jiaying Zhang, Huan Chang, et al.
BMJ Open (2022) Vol. 12, Iss. 9, pp. e061457-e061457
Open Access | Times Cited: 5
Tracking Neutrophil Migration in Zebrafish Model Using Multi-Channel Feature Learning
Marzieh R. Moghadam, Yi‐Ping Phoebe Chen
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 25, Iss. 4, pp. 1197-1205
Closed Access | Times Cited: 7
A holistic AI-based approach for pharmacovigilance optimization from patients behavior on social media
Valentin Roche, Jean-Philippe Robert, Hanan Salam
Artificial Intelligence in Medicine (2023) Vol. 144, pp. 102638-102638
Closed Access | Times Cited: 2
Machine learning approaches for predicting the onset time of the adverse drug events in oncology
Mohan Timilsina, Meera Tandan, Vít Nováček
Machine Learning with Applications (2022) Vol. 9, pp. 100367-100367
Open Access | Times Cited: 4
AIE-DRP: Framework with Machine Learning and Deep Learning Models for Adverse Drug Reaction Prediction in Healthcare Use Case
Muhib Anwar Lambay, S. Pakkir Mohideen, B. S. Abdur Rahman
2022 8th International Conference on Advanced Computing and Communication Systems (ICACCS) (2022), pp. 1330-1336
Closed Access | Times Cited: 3
Why Don’t We Adequately Identify and Manage Adverse Drug Reactions despite Having the Needed Information?
Mark J. Kupersmith, Karl Kieburtz
Health (2024) Vol. 16, Iss. 02, pp. 148-159
Open Access
Developing an AI-based prediction model for anaphylactic shock from injection drugs using Japanese real-world data and chemical structure-based analysis
Tomoyuki Enokiya, Kaito Ozaki
DARU Journal of Pharmaceutical Sciences (2024) Vol. 32, Iss. 1, pp. 253-262
Closed Access
An Evolution of Hybrid Bagging Technique in Chemoinformatic and Drug Discovery
Srinivas Aluvala, Jagadevi N Kalshetty, Saif O. Husain, et al.
(2024), pp. 1-4
Closed Access
Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development
Qi Guo, Bo Fu, Yuan Tian, et al.
Current Medical Research and Opinion (2024) Vol. 40, Iss. 9, pp. 1483-1493
Closed Access

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