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:
External Validation of a Machine Learning Model to Predict 6-Month Mortality for Patients With Advanced Solid Tumors
George Chalkidis, Jordan P. McPherson, Anna C. Beck, et al.
JAMA Network Open (2023) Vol. 6, Iss. 8, pp. e2327193-e2327193
Open Access | Times Cited: 7
George Chalkidis, Jordan P. McPherson, Anna C. Beck, et al.
JAMA Network Open (2023) Vol. 6, Iss. 8, pp. e2327193-e2327193
Open Access | Times Cited: 7
Showing 7 citing articles:
Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach
Tianshu Gu, Wensen Pan, Jing Yu, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Tianshu Gu, Wensen Pan, Jing Yu, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches
Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Predicting 30-day mortality with routine blood tests in patients undergoing palliative radiation therapy: A comparison of logistic regression and gradient boosting models
Tae Hoon Lee, Sang Hoon Seo, Hyunju Shin, et al.
Radiotherapy and Oncology (2025), pp. 110830-110830
Closed Access
Tae Hoon Lee, Sang Hoon Seo, Hyunju Shin, et al.
Radiotherapy and Oncology (2025), pp. 110830-110830
Closed Access
Machine learning models including patient-reported outcome data in oncology: a systematic literature review and analysis of their reporting quality
Daniela Krepper, Matteo Cesari, Niclas J. Hubel, et al.
Journal of Patient-Reported Outcomes (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 3
Daniela Krepper, Matteo Cesari, Niclas J. Hubel, et al.
Journal of Patient-Reported Outcomes (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 3
Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach
Catherine J. Staes, Anna C. Beck, George Chalkidis, et al.
Journal of the American Medical Informatics Association (2023) Vol. 31, Iss. 1, pp. 174-187
Open Access | Times Cited: 7
Catherine J. Staes, Anna C. Beck, George Chalkidis, et al.
Journal of the American Medical Informatics Association (2023) Vol. 31, Iss. 1, pp. 174-187
Open Access | Times Cited: 7
Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence–Based Prognosis for Patients With Advanced Solid Tumors
Elizabeth A. Sloss, Jordan P. McPherson, Anna C. Beck, et al.
JCO Clinical Cancer Informatics (2024), Iss. 8
Open Access | Times Cited: 1
Elizabeth A. Sloss, Jordan P. McPherson, Anna C. Beck, et al.
JCO Clinical Cancer Informatics (2024), Iss. 8
Open Access | Times Cited: 1
A Systematic Review of the Applications of Deep Learning for the Interpretation of Positron Emission Tomography Images of Patients with Lymphoma
Theofilos Kanavos, Effrosyni Birbas, Theodoros P. Zanos
Cancers (2024) Vol. 17, Iss. 1, pp. 69-69
Open Access
Theofilos Kanavos, Effrosyni Birbas, Theodoros P. Zanos
Cancers (2024) Vol. 17, Iss. 1, pp. 69-69
Open Access
