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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:

Artificial Intelligence in Cardiovascular Medicine
Karthik Seetharam, Sirish Shrestha, Partho P. Sengupta
Current Treatment Options in Cardiovascular Medicine (2019) Vol. 21, Iss. 5
Open Access | Times Cited: 63

Showing 26-50 of 63 citing articles:

Artificial Intelligence and Its Role in Diagnosing Heart Failure: A Narrative Review
Diptiman Medhi, Sushmitha Reddy Kamidi, Kannuru Paparaju Mamatha Sree, et al.
Cureus (2024)
Open Access | Times Cited: 2
Artificial Intelligence and Machine Learning in Cardiovascular Imaging
Karthik Seetharam, James K. Min
Methodist DeBakey Cardiovascular Journal (2020) Vol. 16, Iss. 4, pp. 263-263
Open Access | Times Cited: 19
Artificial Intelligence in Cardiac Imaging
Karthik Seetharam, Sirish Shrestha, Partho P. Sengupta
US Cardiology Review (2020) Vol. 13, Iss. 2, pp. 110-116
Open Access | Times Cited: 18
Artificial Intelligence Advancements in the Cardiovascular Imaging of Coronary Atherosclerosis
Pedro Covas, Eison De Guzman, Ian R. Barrows, et al.
Frontiers in Cardiovascular Medicine (2022) Vol. 9
Open Access | Times Cited: 11
Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains
Suchismita Swain, Kamalakanta Muduli, Anil Kumar, et al.
International Journal of Industrial Engineering and Operations Management (2023)
Open Access | Times Cited: 6
Current Advancements in Cardiovascular Disease Management using Artificial Intelligence and Machine Learning Models: Current Scenario and Challenges
Karan Bhadri, Niharika Karnik, Pankaj Dhatrak
2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22) (2022), pp. 1-6
Closed Access | Times Cited: 8
Clinical Inference From Cardiovascular Imaging: Paradigm Shift Towards Machine-Based Intelligent Platform
Karthik Seetharam, Nobuyuki Kagiyama, Sirish Shrestha, et al.
Current Treatment Options in Cardiovascular Medicine (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 12
Automated interpretation of the coronary angioscopy with deep convolutional neural networks
Toru Miyoshi, Akinori Higaki, Hideo Kawakami, et al.
Open Heart (2020) Vol. 7, Iss. 1, pp. e001177-e001177
Open Access | Times Cited: 12
The Significance of Parametric Mapping in Advanced Cardiac Imaging
Yeraz Khachatoorian, Anthon Fuisz, William H. Frishman, et al.
Cardiology in Review (2024)
Closed Access | Times Cited: 1
Broadening Perspectives of Artificial Intelligence in Echocardiography
Karthik Seetharam, Harshith Thyagaturu, Gabriel Lora Ferreira, et al.
Cardiology and Therapy (2024) Vol. 13, Iss. 2, pp. 267-279
Open Access | Times Cited: 1
Artificial intelligence in echocardiography: Review and limitations including epistemological concerns
Gültekin Karakuş, Aleks Değirmencioğlu, Navin C. Nanda
Echocardiography (2022) Vol. 39, Iss. 8, pp. 1044-1053
Closed Access | Times Cited: 7
Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation
Ruiqi Geng, Collin Buelo, Mahalakshmi Sundaresan, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 58, Iss. 2, pp. 429-441
Open Access | Times Cited: 7
Clinical applications of artificial intelligence in cardiology on the verge of the decade
Konrad Pieszko, Jarosław Hiczkiewicz, Jan Budzianowski, et al.
Cardiology Journal (2020) Vol. 28, Iss. 3, pp. 460-472
Open Access | Times Cited: 10
A machine learning-based approach for the prediction of periprocedural myocardial infarction by using routine data
Yao Wang, Kangjun Zhu, Ya Li, et al.
Cardiovascular Diagnosis and Therapy (2020) Vol. 10, Iss. 5, pp. 1313-1324
Open Access | Times Cited: 9
Classification of Electrocardiography Hybrid Convolutional Neural Network-Long Short Term Memory with Fully Connected Layer
Dhanagopal Ramachandran, R. Suresh Kumar, Ahmed Alkhayyat, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 6
Machine learning for spatial stratification of progressive cardiovascular dysfunction in a murine model of type 2 diabetes mellitus
Andrya J. Durr, Anna Korol, Quincy A. Hathaway, et al.
PLoS ONE (2023) Vol. 18, Iss. 5, pp. e0285512-e0285512
Open Access | Times Cited: 3
Soft Computing and Machine Learning Techniques for e-Health Data Analytics
Biswajit Brahma, Hemanta Kumar Bhuyan
Studies in computational intelligence (2022), pp. 83-104
Closed Access | Times Cited: 5
Greg, ML – Machine Learning for Healthcare at a Scale
Paola Lapadula, Giansalvatore Mecca, Donatello Santoro, et al.
Health and Technology (2020) Vol. 10, Iss. 6, pp. 1485-1495
Open Access | Times Cited: 6
Role of Deep Learning in Computed Tomography
Yash Garg, Karthik Seetharam, Manjari Sharma, et al.
Cureus (2023)
Open Access | Times Cited: 2
Cephalometric Variables Prediction from Lateral Photographs Between Different Skeletal Patterns Using Regression Artificial Neural Networks
Saif Mauwafak Ali, Hayder F. Saloom, Mohammed Ali Tawfeeq
Turkish Journal of Orthodontics (2022), pp. 101-111
Open Access | Times Cited: 4
Intelligent Technologies for Excellency in Sustainable Operational Performance in the Healthcare Sector
Suchismita Swain, Peter Oyekola, Kamalakanta Muduli
International Journal of Social Ecology and Sustainable Development (2022) Vol. 13, Iss. 5, pp. 1-16
Closed Access | Times Cited: 4
Individualized Patient Risk Stratification Using Machine Learning and Topological Data Analysis
Arnold C.T. Ng, Victoria Delgado, Jeroen J. Bax
JACC. Cardiovascular imaging (2020) Vol. 13, Iss. 5, pp. 1133-1134
Open Access | Times Cited: 5
Response to: Risk stratification for stroke in atrial fibrillation: incorporating neurologists in the comprehensive management
Ammar M. Killu, Bernard J. Gersh
European Heart Journal (2019) Vol. 40, Iss. 36, pp. 3060-3060
Closed Access | Times Cited: 4
Stent interventions for pulmonary artery stenosis improve bi-ventricular flow efficiency in a swine model
Ryan Pewowaruk, Gregory P. Barton, Cody Johnson, et al.
Journal of Cardiovascular Magnetic Resonance (2021) Vol. 23, Iss. 1, pp. 13-13
Open Access | Times Cited: 4
Artificial intelligence and machine learning in cardiovascular computed tomography
Karthik Seetharam, Premila Bhat, Maxine Orris, et al.
World Journal of Cardiology (2021) Vol. 13, Iss. 10, pp. 546-555
Open Access | Times Cited: 4

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