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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:

Systematic Review of Artificial Intelligence in Acute Respiratory Distress Syndrome for COVID-19 Lung Patients: A Biomedical Imaging Perspective
Jasjit S. Suri, Sushant Agarwal, Suneet Gupta, et al.
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 25, Iss. 11, pp. 4128-4139
Open Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Human activity recognition in artificial intelligence framework: a narrative review
Neha Gupta, Suneet Gupta, Rajesh Kumar Pathak, et al.
Artificial Intelligence Review (2022) Vol. 55, Iss. 6, pp. 4755-4808
Open Access | Times Cited: 225
Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment
Narendra N. Khanna, Mahesh Maindarkar, Vijay Viswanathan, et al.
Healthcare (2022) Vol. 10, Iss. 12, pp. 2493-2493
Open Access | Times Cited: 140
An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review
Suchismita Das, Gopal Krishna Nayak, Luca Saba, et al.
Computers in Biology and Medicine (2022) Vol. 143, pp. 105273-105273
Closed Access | Times Cited: 101
Integrative Approaches in Acute Ischemic Stroke: From Symptom Recognition to Future Innovations
Vicențiu Săceleanu, Corneliu Toader, Horia Pleș, et al.
Biomedicines (2023) Vol. 11, Iss. 10, pp. 2617-2617
Open Access | Times Cited: 42
Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review
Jasjit S. Suri, Mrinalini Bhagawati, Sudip Paul, et al.
Computers in Biology and Medicine (2022) Vol. 142, pp. 105204-105204
Open Access | Times Cited: 63
Bias Investigation in Artificial Intelligence Systems for Early Detection of Parkinson’s Disease: A Narrative Review
Sudip Paul, Mahesh Maindarkar, Sanjay Saxena, et al.
Diagnostics (2022) Vol. 12, Iss. 1, pp. 166-166
Open Access | Times Cited: 51
Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework
Biswajit Jena, Sanjay Saxena, Gopal Krishna Nayak, et al.
Cancers (2022) Vol. 14, Iss. 16, pp. 4052-4052
Open Access | Times Cited: 50
Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0
Mohit Agarwal, Sushant Agarwal, Luca Saba, et al.
Computers in Biology and Medicine (2022) Vol. 146, pp. 105571-105571
Open Access | Times Cited: 48
UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias
Jasjit S. Suri, Mrinalini Bhagawati, Sushant Agarwal, et al.
IEEE Access (2022) Vol. 11, pp. 595-645
Open Access | Times Cited: 42
A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review
Jasjit S. Suri, Mrinalini Bhagawati, Sudip Paul, et al.
Diagnostics (2022) Vol. 12, Iss. 3, pp. 722-722
Open Access | Times Cited: 41
Ensemble Deep Learning Derived from Transfer Learning for Classification of COVID-19 Patients on Hybrid Deep-Learning-Based Lung Segmentation: A Data Augmentation and Balancing Framework
Arun Kumar Dubey, Gian Luca Chabert, Alessandro Carriero, et al.
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1954-1954
Open Access | Times Cited: 23
Unseen Artificial Intelligence—Deep Learning Paradigm for Segmentation of Low Atherosclerotic Plaque in Carotid Ultrasound: A Multicenter Cardiovascular Study
Pankaj K. Jain, Neeraj Sharma, Luca Saba, et al.
Diagnostics (2021) Vol. 11, Iss. 12, pp. 2257-2257
Open Access | Times Cited: 47
A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework
Siva Skandha Sanagala, Andrew Nicolaides, Suneet Gupta, et al.
Computers in Biology and Medicine (2021) Vol. 141, pp. 105131-105131
Closed Access | Times Cited: 43
Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm
Pankaj K. Jain, Abhishek Dubey, Luca Saba, et al.
Journal of Cardiovascular Development and Disease (2022) Vol. 9, Iss. 10, pp. 326-326
Open Access | Times Cited: 36
Five Strategies for Bias Estimation in Artificial Intelligence-based Hybrid Deep Learning for Acute Respiratory Distress Syndrome COVID-19 Lung Infected Patients using AP(ai)Bias 2.0: A Systematic Review
Jasjit S. Suri, Sushant Agarwal, Biswajit Jena, et al.
IEEE Transactions on Instrumentation and Measurement (2022), pp. 1-1
Open Access | Times Cited: 35
Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence paradigm for stroke risk assessment
Pankaj K. Jain, Neeraj Sharma, Mannudeep K. Kalra, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 106017-106017
Closed Access | Times Cited: 27
Artificial intelligence bias in medical system designs: a systematic review
Ashish Kumar, Vivekanand Aelgani, Rubeena Vohra, et al.
Multimedia Tools and Applications (2023) Vol. 83, Iss. 6, pp. 18005-18057
Open Access | Times Cited: 19
An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review
Naresh Kumar Nagwani, Jasjit S. Suri
International Journal of Information Management Data Insights (2023) Vol. 3, Iss. 1, pp. 100153-100153
Open Access | Times Cited: 17
Blockchain, artificial intelligence, and healthcare: the tripod of future—a narrative review
Archana Bathula, Suneet Kumar Gupta, M. Suresh, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 9
Open Access | Times Cited: 5
Accuracy of artificial intelligence algorithms in predicting acute respiratory distress syndrome: a systematic review and meta-analysis
Yaxin Xiong, Yuan Gao, Yucheng Qi, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Artificial intelligence based disease diagnosis using ultrasound imaging
Mahesh Maindarkar, Ashish Kumar
Elsevier eBooks (2025), pp. 147-161
Closed Access
Artificial intelligence–based treatment solutions
Mahesh Maindarkar
Elsevier eBooks (2025), pp. 129-144
Closed Access
Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review
Smiksha Munjral, Mahesh Maindarkar, Puneet Ahluwalia, et al.
Diagnostics (2022) Vol. 12, Iss. 5, pp. 1234-1234
Open Access | Times Cited: 25
NeoAI 1.0: Machine learning-based paradigm for prediction of neonatal and infant risk of death
Jagjit S. Teji, Suneet Jain, Suneet Gupta, et al.
Computers in Biology and Medicine (2022) Vol. 147, pp. 105639-105639
Closed Access | Times Cited: 24
Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report
Narendra N. Khanna, Mahesh Maindarkar, Anudeep Puvvula, et al.
Journal of Cardiovascular Development and Disease (2022) Vol. 9, Iss. 8, pp. 268-268
Open Access | Times Cited: 24
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