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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:

Automated bone marrow cytology using deep learning to generate a histogram of cell types
Rohollah Moosavi Tayebi, Youqing Mu, Taher Dehkharghanian, et al.
Communications Medicine (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 65

Showing 1-25 of 65 citing articles:

How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications
Luís Coelho
Bioengineering (2023) Vol. 10, Iss. 12, pp. 1435-1435
Open Access | Times Cited: 137
Challenges in developing cell culture media using machine learning
Takamasa Hashizume, Bei‐Wen Ying
Biotechnology Advances (2023) Vol. 70, pp. 108293-108293
Open Access | Times Cited: 15
Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions
Tuan D. Pham, Muy‐Teck Teh, Domniki Chatzopoulou, et al.
Current Oncology (2024) Vol. 31, Iss. 9, pp. 5255-5290
Open Access | Times Cited: 5
How I diagnose and treat patients in the pre-fibrotic phase of primary myelofibrosis (pre-PMF) - practical approaches of a German expert panel discussion in 2024
Martin Grießhammer, Haifa Kathrin Al‐Ali, Jan‐Niklas Eckardt, et al.
Annals of Hematology (2025)
Open Access
Annotation-free deep learning for predicting gene mutations from whole slide images of acute myeloid leukemia
Bo-Han Wei, Cheng‐Hong Tsai, Kuo-Jui Sun, et al.
npj Precision Oncology (2025) Vol. 9, Iss. 1
Open Access
Selecting a digitization device for bone marrow aspirate smears
Farina Kock, Martina Pontones, Tabita Ghete, et al.
Laboratory Investigation (2025), pp. 104114-104114
Open Access
Climate change and tuberculosis: an analytical framework
Matthew Saunders, Delia Boccia, Palwasha Khan, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
The puzzling Spitz tumours: is artificial intelligence the key to their understanding?
Laëtitia Launet, Adrián Colomer, Andrés Mosquera‐Zamudio, et al.
Histopathology (2025)
Closed Access
Artificial intelligence in haematopathology: current perspective and future directions
Carlo Pescia, Anna M. Sozanska, Emily Thomas, et al.
Diagnostic histopathology (2025)
Closed Access
An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears
Joshua E. Lewis, Conrad W. Shebelut, Bradley Drumheller, et al.
Modern Pathology (2023) Vol. 36, Iss. 2, pp. 100003-100003
Open Access | Times Cited: 13
An Intelligent Attention-Based Transfer Learning Model for Accurate Differentiation of Bone Marrow Stains to Diagnose Hematological Disorder
Hani Alshahrani, Gunjan Sharma, Vatsala Anand, et al.
Life (2023) Vol. 13, Iss. 10, pp. 2091-2091
Open Access | Times Cited: 12
Optimized Deep Learning Networks for Accurate Identification of Cancer Cells in Bone Marrow
K. Venkatachalam, Vladimir Šimić, Nebojša Bačanin, et al.
Neural Networks (2024) Vol. 181, pp. 106822-106822
Closed Access | Times Cited: 3
Applied machine learning in hematopathology
Taher Dehkharghanian, Youqing Mu, Hamid R. Tizhoosh, et al.
International Journal of Laboratory Hematology (2023) Vol. 45, Iss. S2, pp. 87-94
Open Access | Times Cited: 9
Advancements in computer vision and pathology: Unraveling the potential of artificial intelligence for precision diagnosis and beyond
Justin Chang, Bryce Hatfield
Advances in cancer research (2024), pp. 431-478
Closed Access | Times Cited: 2
A study on the diagnosis of the Helicobacter pylori coccoid form with artificial intelligence technology
Zishao Zhong, Xin Wang, Jianmin Li, et al.
Frontiers in Microbiology (2022) Vol. 13
Open Access | Times Cited: 13
HematoNet: Expert level classification of bone marrow cytology morphology in hematological malignancy with deep learning
Satvik Tripathi, Alisha Isabelle Augustin, Rithvik Sukumaran, et al.
Artificial Intelligence in the Life Sciences (2022) Vol. 2, pp. 100043-100043
Open Access | Times Cited: 12
Digital Microscopy Augmented by Artificial Intelligence to Interpret Bone Marrow Samples for Hematological Diseases
David Bermejo-Peláez, Sandra Rueda Charro, María García Roa, et al.
Microscopy and Microanalysis (2024) Vol. 30, Iss. 1, pp. 151-159
Open Access | Times Cited: 2
An improved Yolov5s based on transformer backbone network for detection and classification of bronchoalveolar lavage cells
Puzhen Wu, Zhe Weng, Wenting Luo, et al.
Computational and Structural Biotechnology Journal (2023) Vol. 21, pp. 2985-3001
Open Access | Times Cited: 6
Circulating Cell-Free RNA in Blood as a Host Response Biomarker for the Detection of Tuberculosis
Adrienne Chang, Conor J. Loy, Joan Sesing Lenz, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 5
Digital assessment of peripheral blood and bone marrow aspirate smears
Joshua E. Lewis, Olga Pozdnyakova
International Journal of Laboratory Hematology (2023) Vol. 45, Iss. S2, pp. 50-58
Open Access | Times Cited: 5
Bone Cancer Detection and Classification Using Owl Search Algorithm With Deep Learning on X-Ray Images
Eatedal Alabdulkreem, Muhammad Kashif Saeed, Saud S. Alotaibi, et al.
IEEE Access (2023) Vol. 11, pp. 109095-109103
Open Access | Times Cited: 5
PHARAOH: A collaborative crowdsourcing platform for PHenotyping And Regional Analysis Of Histology
Kevin Faust, Min Li Chen, Parsa Babaei Zadeh, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data
Carina Agerbo Rosenberg, Matthew A. Rodrigues, Marie Bill, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Deep Learning in Hematology: From Molecules to Patients
Jiasheng Wang
Clinical Hematology International (2024) Vol. 6, Iss. 4
Open Access | Times Cited: 1
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