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:

Breast cancer detection using enhanced IRI-numerical engine and inverse heat transfer modeling: model description and clinical validation
Carlos Gutiérrez, Alyssa Owens, Lori Medeiros, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5

Showing 5 citing articles:

Influence of thermal contrast and limitations of a deep-learning based estimation of early-stage tumour parameters in different breast shapes using simulated passive and dynamic thermography
Mateus Felipe Benicio Moraes, Стефано Сфарра, Henrique Fernandes, et al.
Thermal Science and Engineering Progress (2025), pp. 103418-103418
Open Access

Breast Cancer Screening Using Inverse Modeling of Surface Temperatures and Steady-State Thermal Imaging
Nithya Sritharan, Carlos Gutiérrez, Isaac Perez‐Raya, et al.
Cancers (2024) Vol. 16, Iss. 12, pp. 2264-2264
Open Access | Times Cited: 1

A Transformative Approach for Breast Cancer Detection Using Physics-Informed Neural Network and Surface Temperature Data
Isaac Perez‐Raya, Carlos Gutiérrez, Satish G. Kandlikar
ASME Journal of Heat and Mass Transfer (2024) Vol. 146, Iss. 10
Closed Access

Detectability of Breast Cancer Through Inverse Heat Transfer Modeling Using Patient-Specific Surface Temperatures
Carlos Gutiérrez, Satish G. Kandlikar
Journal of Engineering and Science in Medical Diagnostics and Therapy (2024) Vol. 8, Iss. 1
Closed Access

Assessment of the Breast Density Prevalence in Swiss Women with a Deep Convolutional Neural Network: A Cross-Sectional Study
Adergicia V. Kaiser, Daniela Zanolin-Purin, Natalie Chuck, et al.
Diagnostics (2024) Vol. 14, Iss. 19, pp. 2212-2212
Open Access

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