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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:

A Review of Machine Learning Techniques for the Classification and Detection of Breast Cancer from Medical Images
Reem Jalloul, H. K. Chethan, Ramez Alkhatib
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2460-2460
Open Access | Times Cited: 21

Showing 21 citing articles:

An Overview on the Advancements of Support Vector Machine Models in Healthcare Applications: A Review
Rosita Guido, Stefania Ferrisi, Danilo Lofaro, et al.
Information (2024) Vol. 15, Iss. 4, pp. 235-235
Open Access | Times Cited: 33
Artificial Intelligence in IR Thermal Imaging and Sensing for Medical Applications
A. Nowakowski, Mariusz Kaczmarek
Sensors (2025) Vol. 25, Iss. 3, pp. 891-891
Open Access | Times Cited: 1
Deep learning applications in breast cancer histopathological imaging: diagnosis, treatment, and prognosis
Bitao Jiang, Lingling Bao, Songqin He, et al.
Breast Cancer Research (2024) Vol. 26, Iss. 1
Open Access | Times Cited: 5
Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges
Alessia Mondello, Michele Dal Bo, Giuseppe Toffoli, et al.
Frontiers in Pharmacology (2024) Vol. 14
Open Access | Times Cited: 4
Data Management in Biobanking: Strategies, Challenges, and Future Directions
Ramez Alkhatib, Karoline I. Gaede
BioTech (2024) Vol. 13, Iss. 3, pp. 34-34
Open Access | Times Cited: 4
Machine learning techniques in breast cancer preventive diagnosis: a review
Giada Anastasi, Michela Franchini, Stefania Pieroni, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 35, pp. 82805-82848
Open Access | Times Cited: 2
XAI-driven CatBoost multi-layer perceptron neural network for analyzing breast cancer
Parvathaneni Naga Srinivasu, G. Jaya Lakshmi, Abhishek Gudipalli, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Breast lesions segmentation and classification in a two-stage process based on Mask-RCNN and Transfer Learning
Hama Soltani, Mohamed Amroune, Issam Bendib, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 35763-35780
Closed Access | Times Cited: 6
The Use of Hybrid CNN-RNN Deep Learning Models to Discriminate Tumor Tissue in Dynamic Breast Thermography
Andrés Munguía-Siu, Irene Vergara, Juan Horacio Espinoza-Rodríguez
Journal of Imaging (2024) Vol. 10, Iss. 12, pp. 329-329
Open Access | Times Cited: 1
A deep convolutional neural network for the classification of imbalanced breast cancer dataset
Robert B. Eshun, Marwan Bikdash, Amirul Islam
Healthcare Analytics (2024) Vol. 5, pp. 100330-100330
Open Access | Times Cited: 1
Decoding Breast Cancer: Using Radiomics to Non-Invasively Unveil Molecular Subtypes Directly from Mammographic Images
Manon A. G. Bakker, Maria de Lurdes Ovalho, Nuno Matela, et al.
Journal of Imaging (2024) Vol. 10, Iss. 9, pp. 218-218
Open Access | Times Cited: 1
A COMPARATIVE STUDY OF MACHINE LEARNING AND DEEP LEARNING ALGORITHMS FOR THE DETECTION AND CLASSIFICATION OF BREAST CANCER FROM MAMMOGRAPHY IMAGES AND ULTRA SOUND IMAGES

International Research Journal of Modernization in Engineering Technology and Science (2024)
Open Access
Comparative analysis of features and classification techniques in breast cancer detection for Biglycan biomarker images
Jumana Ma’touq, Nasim Alnuman
Cancer Biomarkers (2024) Vol. 40, Iss. 3-4, pp. 263-273
Open Access
The Need for Standards in Evaluating the Quality of Electronic Health Records and Dental Records: A Narrative Review
Varadraj P. Gurupur, Giang T. Vu, Veena Mayya, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 12, pp. 168-168
Open Access
Breast cancer diagnosis using machine learning techniques
Dildora Muhamediyeva, Shaazizova Madina, Doshchanova Malika
(2024), pp. 15-15
Closed Access
Measurement Methodology: Breast Abnormality Detection using Thermography: An Engineer's Perspective
Ankita Dey, Sreeraman Rajan
IEEE Instrumentation & Measurement Magazine (2024) Vol. 27, Iss. 4, pp. 13-21
Closed Access
A Comprehensive Review on Machine Learning in Breast Cancer Analysis
U Ananthanagu, P M Ebin, R. Chinnaiyan
Lecture notes in electrical engineering (2024), pp. 565-575
Closed Access
Advancements in Breast Cancer Diagnosis: A Comprehensive Review of Mammography Datasets, Preprocessing and Classification Techniques
Hama Soltani, Issam Bendib, Mohamed Yassine Haouam, et al.
Acta Informatica Pragensia (2024) Vol. 13, Iss. 2, pp. 308-326
Open Access
From Pixels to Prognosis: Exploring from UNet to Segment Anything in Mammogram Image Processing for Tumor Segmentation
M R Hithesh, Vishwanath Kadaba Puttanna
(2024), pp. 1-7
Closed Access
Accurate breast cancer diagnosis strategy (BCDS) based on deep learning techniques
Taghreed S. Ibrahim, Mohamed S. Saraya, Ahmed I. Saleh, et al.
Neural Computing and Applications (2024)
Closed Access
Enhancing Early Breast Cancer Detection with Infrared Thermography: A Comparative Evaluation of Deep Learning and Machine Learning Models
Reem Jalloul, Chethan Hasigala Krishnappa, Victor Ikechukwu Agughasi, et al.
Technologies (2024) Vol. 13, Iss. 1, pp. 7-7
Open Access
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