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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 microscopic analysis of blood cells for disease detection with AI perspective
Nilkanth Mukund Deshpande, Shilpa Gite, Rajanikanth Aluvalu
PeerJ Computer Science (2021) Vol. 7, pp. e460-e460
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

An Efficient Multi-Level Convolutional Neural Network Approach for White Blood Cells Classification
César Cheuque, Marvin Querales, Roberto León, et al.
Diagnostics (2022) Vol. 12, Iss. 2, pp. 248-248
Open Access | Times Cited: 64
Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review
Tanzilal Mustaqim, Chastine Fatichah, Nanik Suciati
IEEE Access (2023) Vol. 11, pp. 16108-16127
Open Access | Times Cited: 26
Advances in Microfluidics for Single Red Blood Cell Analysis
Georgii V. Grigorev, А. И. Лебедев, Xiaohao Wang, et al.
Biosensors (2023) Vol. 13, Iss. 1, pp. 117-117
Open Access | Times Cited: 20
Bio-net dataset: AI-based diagnostic solutions using peripheral blood smear images
Usman Ali Shams, Isma Javed, Muhammad Fizan, et al.
Blood Cells Molecules and Diseases (2024) Vol. 105, pp. 102823-102823
Closed Access | Times Cited: 5
Deepening into the suitability of using pre-trained models of ImageNet against a lightweight convolutional neural network in medical imaging: an experimental study
Laith Alzubaidi, Ye Duan, Ayad Q. Al-Dujaili, et al.
PeerJ Computer Science (2021) Vol. 7, pp. e715-e715
Open Access | Times Cited: 39
Automatic Blood Cell Detection Based on Advanced YOLOv5s Network
Yinggang He
IEEE Access (2024) Vol. 12, pp. 17639-17650
Open Access | Times Cited: 4
Quantitative Imaging of Colloidal Structures
Jason Conradt, Eric M. Furst
Langmuir (2025)
Closed Access
Blood cells identification in microscopic images based on hybrid approach
Veska Georgieva, Plamen Petrov, Lorina Karaminova
AIP conference proceedings (2025) Vol. 3303, pp. 060005-060005
Closed Access
FocusAugMix: A Data Augmentation Method for Enhancing Acute Lymphoblastic Leukemia Classification
Tanzilal Mustaqim, Chastine Fatichah, Nanik Suciati, et al.
Intelligent Systems with Applications (2025), pp. 200512-200512
Open Access
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
Improved Otsu and Kapur approach for white blood cells segmentation based on LebTLBO optimization for the detection of Leukemia
Nilkanth Mukund Deshpande, Shilpa Gite, Biswajeet Pradhan, et al.
Mathematical Biosciences & Engineering (2021) Vol. 19, Iss. 2, pp. 1970-2001
Open Access | Times Cited: 24
A review on computer aided detection and classification of leukemia
K. Anilkumar, Vasupalli Manoj, Tomer Sagi
Multimedia Tools and Applications (2023) Vol. 83, Iss. 6, pp. 17961-17981
Closed Access | Times Cited: 9
Deep learning enhances acute lymphoblastic leukemia diagnosis and classification using bone marrow images
Basel Elsayed, Mohamed Elhadary, Raghad Mohamed Elshoeibi, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 9
Advancing instance segmentation and WBC classification in peripheral blood smear through domain adaptation: A study on PBC and the novel RV-PBS datasets
Jimut Bahan Pal, Aniket Bhattacharyea, Debasis Banerjee, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123660-123660
Closed Access | Times Cited: 3
Advanced Convolutional Neural Networks for Precise White Blood Cell Subtype Classification in Medical Diagnostics
Athanasios Kanavos, Orestis Papadimitriou, Khalil Al-Hussaeni, et al.
Electronics (2024) Vol. 13, Iss. 14, pp. 2818-2818
Open Access | Times Cited: 3
White Blood Cell Classification Using Multi-Attention Data Augmentation and Regularization
Nasrin Bayat, Diane D. Davey, Melanie Coathup, et al.
Big Data and Cognitive Computing (2022) Vol. 6, Iss. 4, pp. 122-122
Open Access | Times Cited: 12
RedTell: an AI tool for interpretable analysis of red blood cell morphology
Ario Sadafi, Maria Bordukova, Asya Makhro, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 7
Digital morphology in hematology diagnosis and education: The experience of the European LeukemiaNet WP10
Gina Zini, Ombretta Barbagallo, Fernando Scavone, et al.
International Journal of Laboratory Hematology (2022) Vol. 44, Iss. S1, pp. 37-44
Closed Access | Times Cited: 11
Artificial intelligence and the blood film: Performance of the MC‐80 digital morphology analyzer in samples with neoplastic and reactive cell types
Gina Zini, Francesca Mancini, Elena Rossi, et al.
International Journal of Laboratory Hematology (2023) Vol. 45, Iss. 6, pp. 881-889
Open Access | Times Cited: 5
Explainable Artificial Intelligence–A New Step towards the Trust in Medical Diagnosis with AI Frameworks: A Review
Nilkanth Mukund Deshpande, Shilpa Gite, Biswajeet Pradhan, et al.
Computer Modeling in Engineering & Sciences (2022) Vol. 133, Iss. 3, pp. 843-872
Open Access | Times Cited: 9
An Artificial Intelligence Approach for Data Modelling Patients Inheritance of Sickle Cell Disease (SCD) in the Eastern Regions of Saudi Arabia
Mohammed Gollapalli, Aljawharah Alfaleh
Mathematical Modelling and Engineering Problems (2022) Vol. 9, Iss. 4, pp. 1079-1088
Open Access | Times Cited: 9
Label-free in-vivo classification and tracking of red blood cells and platelets using Dynamic-YOLOv4 network
Caizhong Guan, Bin He, Hongting Zhang, et al.
Journal of Innovative Optical Health Sciences (2024) Vol. 17, Iss. 05
Open Access | Times Cited: 1
Automated White Blood Cell Disease Recognition Using Lightweight Deep Learning
Abdullah Alqahtani, Shtwai Alsubai, Mohemmed Sha, et al.
Computer Systems Science and Engineering (2023) Vol. 46, Iss. 1, pp. 107-123
Open Access | Times Cited: 4
Microscopic Analysis of Blood Cells for Disease Detection: A Review
Nilkanth Mukund Deshpande, Shilpa Gite, Rajanikanth Aluvalu
Intelligent systems reference library (2021), pp. 125-151
Closed Access | Times Cited: 6
An automated approach for fibroblast cell confluency characterisation and sample handling using AIoT for bio-research and bio-manufacturing
Muaadh Shamhan, Ahmad Syahrin Idris, Siti Fauziah Toha, et al.
Cogent Engineering (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 2
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