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 guided physician directive improves head and neck planning quality and practice Uniformity: A prospective study
Maryam Mashayekhi, Rafe McBeth, Dan Nguyen, et al.
Clinical and Translational Radiation Oncology (2023) Vol. 40, pp. 100616-100616
Open Access | Times Cited: 11

Showing 11 citing articles:

Enhancing head and neck tumor management with artificial intelligence: Integration and perspectives
Nian‐Nian Zhong, Hanqi Wang, Xin-Yue Huang, et al.
Seminars in Cancer Biology (2023) Vol. 95, pp. 52-74
Closed Access | Times Cited: 39

A review of dose prediction methods for tumor radiation therapy
Xiaoyan Kui, Fang Liu, Min Yang, et al.
Meta-Radiology (2024) Vol. 2, Iss. 1, pp. 100057-100057
Open Access | Times Cited: 9

Evaluating machine learning enhanced intelligent‐optimization‐engine (IOE) performance for ethos head‐and‐neck (HN) plan generation
Justin Visak, Enobong Inam, Boyu Meng, et al.
Journal of Applied Clinical Medical Physics (2023) Vol. 24, Iss. 7
Open Access | Times Cited: 15

In silico evaluation and feasibility of near margin-less head and neck daily adaptive radiotherapy
Michael Dohopolski, Justin Visak, Choi ByongSu, et al.
Radiotherapy and Oncology (2024) Vol. 197, pp. 110178-110178
Closed Access | Times Cited: 4

Closing the gap in plan quality: Leveraging deep‐learning dose prediction for adaptive radiotherapy
Sean Domal, Austen Maniscalco, Justin Visak, et al.
Journal of Applied Clinical Medical Physics (2025)
Open Access

Clinical implementation of deep learning robust IMPT planning in oropharyngeal cancer patients: A blinded clinical study
Ilse G. van Bruggen, M. van Dijk, Minke J Brinkman-Akker, et al.
Radiotherapy and Oncology (2024) Vol. 200, pp. 110522-110522
Open Access | Times Cited: 2

Single patient learning for adaptive radiotherapy dose prediction
Austen Maniscalco, Xiao Liang, Mu‐Han Lin, et al.
Medical Physics (2023) Vol. 50, Iss. 12, pp. 7324-7337
Open Access | Times Cited: 5

Can input reconstruction be used to directly estimate uncertainty of a dose prediction U‐Net model?
Margerie Huet‐Dastarac, Dan Nguyen, E. Longton, et al.
Medical Physics (2024) Vol. 51, Iss. 10, pp. 7369-7377
Closed Access | Times Cited: 1

Deep learning dose prediction to approach Erasmus-iCycle dosimetric plan quality within seconds for instantaneous treatment planning
Joep van Genderingen, Dan Nguyen, Franziska Knuth, et al.
Radiotherapy and Oncology (2024) Vol. 203, pp. 110662-110662
Closed Access

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