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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:

Supervised Machine Learning: A Brief Primer
Tammy Jiang, Jaimie L. Gradus, Anthony J. Rosellini
Behavior Therapy (2020) Vol. 51, Iss. 5, pp. 675-687
Open Access | Times Cited: 506

Showing 1-25 of 506 citing articles:

Using machine learning approaches for multi-omics data analysis: A review
Parminder Singh Reel, Smarti Reel, Ewan R. Pearson, et al.
Biotechnology Advances (2021) Vol. 49, pp. 107739-107739
Open Access | Times Cited: 520
Generative Adversarial Networks
Amey Thakur
International Journal for Research in Applied Science and Engineering Technology (2021) Vol. 9, Iss. 8, pp. 2307-2325
Open Access | Times Cited: 176
Using machine learning for healthcare challenges and opportunities
Abdullah Alanazi
Informatics in Medicine Unlocked (2022) Vol. 30, pp. 100924-100924
Open Access | Times Cited: 139
A Review of Machine Learning and Deep Learning Approaches on Mental Health Diagnosis
Ngumimi Karen Iyortsuun, Soo-Hyung Kim, Min Jhon, et al.
Healthcare (2023) Vol. 11, Iss. 3, pp. 285-285
Open Access | Times Cited: 119
The cognitive and perceptual correlates of ideological attitudes: a data-driven approach
Leor Zmigrod, Ian W. Eisenberg, Patrick G. Bissett, et al.
Philosophical Transactions of the Royal Society B Biological Sciences (2021) Vol. 376, Iss. 1822, pp. 20200424-20200424
Open Access | Times Cited: 111
Machine learning in the quantum realm: The state-of-the-art, challenges, and future vision
Essam H. Houssein, Zainab Abohashima, Mohamed Elhoseny, et al.
Expert Systems with Applications (2022) Vol. 194, pp. 116512-116512
Closed Access | Times Cited: 96
New Opportunity: Machine Learning for Polymer Materials Design and Discovery
Pengcheng Xu, Huimin Chen, Minjie Li, et al.
Advanced Theory and Simulations (2022) Vol. 5, Iss. 5
Closed Access | Times Cited: 77
Artificial intelligence in pancreatic cancer
Bowen Huang, Haoran Huang, Shuting Zhang, et al.
Theranostics (2022) Vol. 12, Iss. 16, pp. 6931-6954
Open Access | Times Cited: 70
A guide to artificial intelligence for cancer researchers
Raquel Pérez-López, Narmin Ghaffari Laleh, Faisal Mahmood, et al.
Nature reviews. Cancer (2024) Vol. 24, Iss. 6, pp. 427-441
Closed Access | Times Cited: 64
Foundations of Machine Learning
Vishal Goar, Nagendra Singh Yadav
Advances in business information systems and analytics book series (2024), pp. 25-48
Closed Access | Times Cited: 55
A Comprehensive Survey of Machine Learning Methodologies with Emphasis in Water Resources Management
Maria Drogkoula, Konstantinos Kokkinos, Nicholas Samaras
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12147-12147
Open Access | Times Cited: 50
Neural Networks And Machine Learning
Anu Sayal, Janhvi Jha, N Chaithra, et al.
(2023), pp. 58-63
Closed Access | Times Cited: 50
On the importance of interpretable machine learning predictions to inform clinical decision making in oncology
Sheng-Chieh Lu, Christine L. Swisher, Caroline Chung, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 47
Anti-Cancer Peptides: Status and Future Prospects
Gehane Ghaly, Hatem Tallima, Eslam Dabbish, et al.
Molecules (2023) Vol. 28, Iss. 3, pp. 1148-1148
Open Access | Times Cited: 42
Introduction to Machine Learning
Manish Kumar, Bhawna Verma
Studies in computational intelligence (2024), pp. 51-94
Closed Access | Times Cited: 42
Role of Machine Learning Assisted Biosensors in Point-of-Care-Testing For Clinical Decisions
Manish Bhaiyya, Debdatta Panigrahi, Prakash Rewatkar, et al.
ACS Sensors (2024) Vol. 9, Iss. 9, pp. 4495-4519
Open Access | Times Cited: 21
Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities
Connor D. Flynn, Dingran Chang
Diagnostics (2024) Vol. 14, Iss. 11, pp. 1100-1100
Open Access | Times Cited: 17
Machine learning applications in catalytic hydrogenation of carbon dioxide to methanol: A comprehensive review
Ermias Girma Aklilu, Tijani Bounahmidi
International Journal of Hydrogen Energy (2024) Vol. 61, pp. 578-602
Closed Access | Times Cited: 16
Hybrid Techniques to Predict Solar Radiation Using Support Vector Machine and Search Optimization Algorithms: A Review
José M. Álvarez-Alvarado, José Gabriel Ríos-Moreno, Saúl Antonio Obregón Biosca, et al.
Applied Sciences (2021) Vol. 11, Iss. 3, pp. 1044-1044
Open Access | Times Cited: 65
Detecting and Measuring Depression on Social Media Using a Machine Learning Approach: Systematic Review
Danxia Liu, Xing Lin Feng, Farooq Ahmed, et al.
JMIR Mental Health (2021) Vol. 9, Iss. 3, pp. e27244-e27244
Open Access | Times Cited: 59
Machine learning: its challenges and opportunities in plant system biology
Mohsen Hesami, Milad Alizadeh, Andrew Maxwell Phineas Jones, et al.
Applied Microbiology and Biotechnology (2022) Vol. 106, Iss. 9-10, pp. 3507-3530
Closed Access | Times Cited: 52
Predictive models for clinical decision making: Deep dives in practical machine learning
Sandra Eloranta, Magnus Boman
Journal of Internal Medicine (2022) Vol. 292, Iss. 2, pp. 278-295
Open Access | Times Cited: 46
Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Function in an SDN Network
Senthil Prabakaran, R. Ramalakshmi, Irshad Hussain, et al.
Sensors (2022) Vol. 22, Iss. 3, pp. 709-709
Open Access | Times Cited: 45
Interpretable machine learning methods for predictions in systems biology from omics data
David Sidak, Jana Schwarzerová, Wolfram Weckwerth, et al.
Frontiers in Molecular Biosciences (2022) Vol. 9
Open Access | Times Cited: 42
Leveraging machine learning and blockchain in E-commerce and beyond: benefits, models, and application
Hrag Jebamikyous, Menglu Li, Yoga Suhas, et al.
Discover Artificial Intelligence (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 40
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