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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:

The emerging roles of artificial intelligence in cancer drug development and precision therapy
Guosheng Liang, Wenguo Fan, Hui Luo, et al.
Biomedicine & Pharmacotherapy (2020) Vol. 128, pp. 110255-110255
Open Access | Times Cited: 115

Showing 1-25 of 115 citing articles:

Targeting HER2-positive breast cancer: advances and future directions
Sandra M. Swain, Mythili Shastry, Erika Hamilton
Nature Reviews Drug Discovery (2022) Vol. 22, Iss. 2, pp. 101-126
Open Access | Times Cited: 544
Artificial intelligence (AI) and big data in cancer and precision oncology
Zodwa Dlamini, Flavia Zita Francies, Rodney Hull, et al.
Computational and Structural Biotechnology Journal (2020) Vol. 18, pp. 2300-2311
Open Access | Times Cited: 262
Application of Artificial Intelligence in Medicine: An Overview
Pengran Liu, Lin Lu, Jiayao Zhang, et al.
Current Medical Science (2021) Vol. 41, Iss. 6, pp. 1105-1115
Open Access | Times Cited: 166
Using ChatGPT in Medical Research: Current Status and Future Directions
Suebsarn Ruksakulpiwat, Ayanesh Kumar, Anuoluwapo Ajibade
Journal of Multidisciplinary Healthcare (2023) Vol. Volume 16, pp. 1513-1520
Open Access | Times Cited: 116
The promising interplay between sonodynamic therapy and nanomedicine
Roberto Canaparo, Federica Foglietta, Nadia Barbero, et al.
Advanced Drug Delivery Reviews (2022) Vol. 189, pp. 114495-114495
Closed Access | Times Cited: 95
An Overview of Artificial Intelligence in Oncology
Eduardo Moreno Júdice de Mattos Farina, Jacqueline Justino Nabhen, Maria Inez Dacoregio, et al.
Future Science OA (2022) Vol. 8, Iss. 4
Open Access | Times Cited: 73
Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective
Muhammad Sufyan, Zeeshan Shokat, Usman Ali Ashfaq
Computers in Biology and Medicine (2023) Vol. 165, pp. 107356-107356
Closed Access | Times Cited: 71
Nanoparticle-mediated cancer cell therapy: basic science to clinical applications
Jaya Verma, Caaisha Warsame, Rajkumar Kottayasamy Seenivasagam, et al.
Cancer and Metastasis Reviews (2023) Vol. 42, Iss. 3, pp. 601-627
Open Access | Times Cited: 57
Simulation-based approaches for drug delivery systems: Navigating advancements, opportunities, and challenges
Iman Salahshoori, Mahdi Golriz, Marcos A.L. Nobre, et al.
Journal of Molecular Liquids (2023) Vol. 395, pp. 123888-123888
Open Access | Times Cited: 52
Exploiting bacteria for cancer immunotherapy
Seong Young Kwon, Hien Thi-Thu Ngo, Jinbae Son, et al.
Nature Reviews Clinical Oncology (2024) Vol. 21, Iss. 8, pp. 569-589
Closed Access | Times Cited: 48
Unraveling the tumor microenvironment: Insights into cancer metastasis and therapeutic strategies
Mohamed El‐Tanani, Syed Arman Rabbani, Rasha Babiker, et al.
Cancer Letters (2024) Vol. 591, pp. 216894-216894
Open Access | Times Cited: 46
Integration of artificial intelligence in lung cancer: Rise of the machine
Colton Ladbury, Arya Amini, Ameish Govindarajan, et al.
Cell Reports Medicine (2023) Vol. 4, Iss. 2, pp. 100933-100933
Open Access | Times Cited: 44
The potential application of artificial intelligence in veterinary clinical practice and biomedical research
Olalekan Chris Akinsulie, Ibrahim Idris, Victor Ayodele Aliyu, et al.
Frontiers in Veterinary Science (2024) Vol. 11
Open Access | Times Cited: 22
Learning Health Systems
Thomas Foley, Leora I. Horwitz
(2025)
Closed Access | Times Cited: 2
Breakthrough in targeted therapy for non-small cell lung cancer
Zhencong Ye, Yongmei Huang, Jianhao Ke, et al.
Biomedicine & Pharmacotherapy (2020) Vol. 133, pp. 111079-111079
Open Access | Times Cited: 81
Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis
Andrew James Codlin, Thang Phuoc Dao, Luan Nguyen Quang Vo, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 74
Advancements in Oncology with Artificial Intelligence—A Review Article
Nikitha Vobugari, Vikranth Raja, Udhav Sethi, et al.
Cancers (2022) Vol. 14, Iss. 5, pp. 1349-1349
Open Access | Times Cited: 57
Understanding Drug Sensitivity and Tackling Resistance in Cancer
Jeffrey W. Tyner, Franziska Haderk, Anbarasu Kumaraswamy, et al.
Cancer Research (2022) Vol. 82, Iss. 8, pp. 1448-1460
Open Access | Times Cited: 42
High-dimensional role of AI and machine learning in cancer research
Enrico Capobianco
British Journal of Cancer (2022) Vol. 126, Iss. 4, pp. 523-532
Open Access | Times Cited: 41
Using artificial intelligence technology to fight COVID-19: a review
Yong Peng, Enbin Liu, Shanbi Peng, et al.
Artificial Intelligence Review (2022) Vol. 55, Iss. 6, pp. 4941-4977
Open Access | Times Cited: 39
Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine
Vivek Bhakta Mathema, Partho Sen, Santosh Lamichhane, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 1372-1382
Open Access | Times Cited: 39
A framework for understanding, designing, developing and evaluating learning health systems
Tom Foley, Luke Vale
Learning Health Systems (2022) Vol. 7, Iss. 1
Open Access | Times Cited: 38
Cross-dimensional transfer learning in medical image segmentation with deep learning
Hicham Messaoudi, Ahror Belaid, D. Ben Salem, et al.
Medical Image Analysis (2023) Vol. 88, pp. 102868-102868
Open Access | Times Cited: 23
Data to knowledge to improvement: creating the learning health system
Paige McDonald, Tom Foley, Robert Verheij, et al.
BMJ (2024), pp. e076175-e076175
Open Access | Times Cited: 13
A systematic review of machine learning methods in software testing
Sedighe Ajorloo, Amirhossein Jamarani, Mehdi Kashfi, et al.
Applied Soft Computing (2024) Vol. 162, pp. 111805-111805
Closed Access | Times Cited: 12
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