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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:

DenseNet for Breast Tumor Classification in Mammographic Images
Yuliana Jiménez-Gaona, María José Rodríguez-Álvarez, Héctor Espinós-Morató, et al.
Lecture notes in computer science (2021), pp. 166-176
Closed Access | Times Cited: 11

Showing 11 citing articles:

Breast Cancer Detection and Localizing the Mass Area Using Deep Learning
Md. Mijanur Rahman, Md. Zihad Bin Jahangir, Anisur Rahman, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 7, pp. 80-80
Open Access | Times Cited: 8
A Heuristic Strategy Assisted Deep Learning Models for Brain Tumor Classification and Abnormality Segmentation
Vinay Kumar, Satya Ranjan Pattanaik, V. V. Sunil Kumar
Computational Intelligence (2025) Vol. 41, Iss. 1
Closed Access
A Multimodal Transfer Learning Approach Using PubMedCLIP for Medical Image Classification
Hong N. Dao, Tuyen D. Nguyen, Chérubin Mugisha, et al.
IEEE Access (2024) Vol. 12, pp. 75496-75507
Closed Access | Times Cited: 4
Multimodal breast cancer hybrid explainable computer-aided diagnosis using medical mammograms and ultrasound Images
Riyadh M. Al-Tam, Aymen M. Al-Hejri, Sultan S. Alshamrani, et al.
Journal of Applied Biomedicine (2024) Vol. 44, Iss. 3, pp. 731-758
Closed Access | Times Cited: 4
Selecting the optimal transfer learning model for precise breast cancer diagnosis utilizing pre-trained deep learning models and histopathology images
Aswathy Ravikumar, Harini Sriraman, B. Saleena, et al.
Health and Technology (2023) Vol. 13, Iss. 5, pp. 721-745
Closed Access | Times Cited: 4
Breast mass regions classification from mammograms using convolutional neural networks and transfer learning.
Yuliana Jiménez-Gaona, María José Rodríguez-Álvarez, Diana Carrión-Figueroa, et al.
Journal of Modern Optics (2023) Vol. 70, Iss. 10, pp. 645-660
Closed Access | Times Cited: 4
Evaluation of filtering and contrast in X-ray and computerized tomography scan lung classification
Anitha Nagaraja Setty, T. M. Rajesh, Krishnatejaswi Shenthar, et al.
Indonesian Journal of Electrical Engineering and Computer Science (2024) Vol. 33, Iss. 3, pp. 1715-1715
Open Access
RM-DenseNet: An Enhanced DenseNet Framework with Residual Model for Breast Cancer Classification Using Mammographic Images
Shahnawaz Khan, Avanith Kanamarlapudi, A. Robert Singh
(2024), pp. 711-715
Closed Access
Cáncer de Mama: Prevalencia, Factores de Riesgo y Métodos Diagnósticos
Angela Katerine Rosero Ordoñez, Andrea Angelina Pincay Francis, Lilibeth Stefany Solorzano Holguín, et al.
Revista Científica Higía de la Salud (2022) Vol. 7, Iss. 2
Open Access | Times Cited: 2
Breast mass segmentation using mammographic data: a systematic review
Harmandeep Singh, Vipul Sharma, Damanpreet Singh
Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (2023), pp. 1-22
Closed Access
Neural Network Software to Process Medical Data Modeling
Egor Emelyanov, Maxim Polyakov
2021 3rd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA) (2021), pp. 580-585
Closed Access
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