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:

Clinical characteristics, risk factors and outcomes of cancer patients withCOVID‐19: A population‐based study
Jiandong Zhou, Ishan Lakhani, Oscar Hou In Chou, et al.
Cancer Medicine (2022) Vol. 12, Iss. 1, pp. 287-296
Open Access | Times Cited: 7

Showing 7 citing articles:

Comparing mortality rates, risk, and trends of hip fracture and common cancers in Hong Kong, 2010–2020: A population-based study
Xiaowen Zhang, Chor‐Wing Sing, Philip Chun-Ming Au, et al.
Osteoporosis and Sarcopenia (2025)
Open Access

The burden of COVID-19 death for different cancer types: a large population-based study
You Mo, Duncan Wei, Xiaozheng Chen, et al.
Journal of Global Health (2025) Vol. 15
Open Access

Population-Based Clinical Studies Using Routinely Collected Data in Hong Kong, China: A Systematic Review of Trends and Established Local Practices
Derek Wu, Ronald Hang Kin Nam, Keith Sai Kit Leung, et al.
Cardiovascular Innovations and Applications (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 10

Clinical Characteristics and Outcomes in Hospitalized Patients with COVID-19 and Cancer History: A Multicenter Cross-Sectional Study in Southwestern Iran
Javad Zarei, Abbas Sheikhtaheri, Mehrnaz Ahmadi, et al.
International Journal of Hematology-Oncology and Stem Cell Research (2024)
Open Access

Insights into cancer characteristics among SARS-CoV-2 infected hospitalized patients: a comprehensive analysis from the National Clinical Registry for COVID-19
S. N. Chatterji, Alka Turuk, Parijat Das, et al.
Journal of Cancer Research and Clinical Oncology (2024) Vol. 150, Iss. 11
Open Access

Development of a novel machine learning model based on laboratory and imaging indices to predict acute cardiac injury in cancer patients with COVID-19 infection: a retrospective observational study
G. Wan, Xuefeng Wu, Xiaowei Zhang, et al.
Journal of Cancer Research and Clinical Oncology (2023) Vol. 149, Iss. 19, pp. 17039-17050
Closed Access | Times Cited: 1

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