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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:

Artificial intelligence for precision oncology: beyond patient stratification
Francisco Azuaje
npj Precision Oncology (2019) Vol. 3, Iss. 1
Open Access | Times Cited: 150

Showing 1-25 of 150 citing articles:

Artificial intelligence: Implications for the future of work
John Howard
American Journal of Industrial Medicine (2019) Vol. 62, Iss. 11, pp. 917-926
Closed Access | Times Cited: 341
Biomarker-guided therapy for colorectal cancer: strength in complexity
Anita Sveen, Scott Kopetz, Ragnhild A. Lothe
Nature Reviews Clinical Oncology (2019) Vol. 17, Iss. 1, pp. 11-32
Open Access | Times Cited: 270
Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
Muhammad Iqbal, Zeeshan Javed, Haleema Sadia, et al.
Cancer Cell International (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 212
Artificial intelligence-based multi-omics analysis fuels cancer precision medicine
Xiujing He, Xiaowei Liu, Fengli Zuo, et al.
Seminars in Cancer Biology (2022) Vol. 88, pp. 187-200
Open Access | Times Cited: 147
Machine learning in the prediction of cancer therapy
Raihan Rafique, S. M. Riazul Islam, Julhash U. Kazi
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 4003-4017
Open Access | Times Cited: 119
BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions
Francisco Maria Calisto, Carlos Santiago, Nuno Nunes, et al.
Artificial Intelligence in Medicine (2022) Vol. 127, pp. 102285-102285
Open Access | Times Cited: 85
Molecular tumour boards — current and future considerations for precision oncology
Apostolia M. Tsimberidou, Michael Kahle, Henry Hiep Vo, et al.
Nature Reviews Clinical Oncology (2023) Vol. 20, Iss. 12, pp. 843-863
Closed Access | Times Cited: 58
A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology
Debabrata Acharya, Anirban Mukhopadhyay
Briefings in Functional Genomics (2024) Vol. 23, Iss. 5, pp. 549-560
Closed Access | Times Cited: 15
Detection and Classification of Pulmonary Nodules Using Convolutional Neural Networks: A Survey
Patrice Monkam, Shouliang Qi, He Ma, et al.
IEEE Access (2019) Vol. 7, pp. 78075-78091
Open Access | Times Cited: 104
Artificial Intelligence (AI)-Based Systems Biology Approaches in Multi-Omics Data Analysis of Cancer
Nupur Biswas, Saikat Chakrabarti
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 104
Deep transfer learning for reducing health care disparities arising from biomedical data inequality
Yan Gao, Yan Cui
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 94
Applied machine learning in cancer research: A systematic review for patient diagnosis, classification and prognosis
Κωνσταντίνα Κούρου, Konstantinos Exarchos, Costas Papaloukas, et al.
Computational and Structural Biotechnology Journal (2021) Vol. 19, pp. 5546-5555
Open Access | Times Cited: 85
Engineered Nanomaterials: The Challenges and Opportunities for Nanomedicines
Fahad Albalawi, Mohd Zobir Hussein, Sharida Fakurazi, et al.
International Journal of Nanomedicine (2021) Vol. Volume 16, pp. 161-184
Open Access | Times Cited: 84
Artificial intelligence in early drug discovery enabling precision medicine
Fabio Boniolo, Emilio Dorigatti, Alexander J. Ohnmacht, et al.
Expert Opinion on Drug Discovery (2021) Vol. 16, Iss. 9, pp. 991-1007
Open Access | Times Cited: 79
A random forest based biomarker discovery and power analysis framework for diagnostics research
Animesh Acharjee, Joseph Larkman, Yuanwei Xu, et al.
BMC Medical Genomics (2020) Vol. 13, Iss. 1
Open Access | Times Cited: 78
From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation
David Valle-Cruz, Vanessa Fernández-Cortez, J. Ramón Gil-García
Government Information Quarterly (2021) Vol. 39, Iss. 2, pp. 101644-101644
Closed Access | Times Cited: 77
Multiplex bioimaging of single-cell spatial profiles for precision cancer diagnostics and therapeutics
Mayar Allam, Shuangyi Cai, Ahmet F. Coskun
npj Precision Oncology (2020) Vol. 4, Iss. 1
Open Access | Times Cited: 76
Convergence of Precision Medicine and Public Health Into Precision Public Health: Toward a Big Data Perspective
Pedro Elkind Velmovitsky, Tatiana Bevilacqua, Paulo Alencar, et al.
Frontiers in Public Health (2021) Vol. 9
Open Access | Times Cited: 57
Prediction models applying machine learning to oral cavity cancer outcomes: A systematic review
John Adeoye, Jia Tan, S. W. Choi, et al.
International Journal of Medical Informatics (2021) Vol. 154, pp. 104557-104557
Closed Access | Times Cited: 57
Just Add Data: automated predictive modeling for knowledge discovery and feature selection
Ioannis Tsamardinos, Paulos Charonyktakis, Γεώργιος Παπουτσόγλου, et al.
npj Precision Oncology (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 56
Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives
Nian‐Nian Zhong, Hanqi Wang, Xinyue Huang, et al.
Seminars in Cancer Biology (2023) Vol. 95, pp. 52-74
Closed Access | Times Cited: 40
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: 39
Hepatocellular carcinoma surveillance: current practice and future directions
Joseph Ahn, Yi‐Te Lee, Vatche G. Agopian, et al.
Hepatoma Research (2022)
Open Access | Times Cited: 39
AI and machine learning in resuscitation: Ongoing research, new concepts, and key challenges
Yohei Okada, Mayli Mertens, Nan Liu, et al.
Resuscitation Plus (2023) Vol. 15, pp. 100435-100435
Open Access | Times Cited: 23
Precision Oncology, Signaling Pathways Reprogramming and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics
Manish Kumar
(2025)
Closed Access | Times Cited: 1
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