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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:

Deep Learning for Health Informatics
Daniele Ravì, Charence Wong, Fani Deligianni, et al.
IEEE Journal of Biomedical and Health Informatics (2016) Vol. 21, Iss. 1, pp. 4-21
Open Access | Times Cited: 1781

Showing 1-25 of 1781 citing articles:

A survey on deep learning in medical image analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, et al.
Medical Image Analysis (2017) Vol. 42, pp. 60-88
Open Access | Times Cited: 11132
Artificial intelligence in healthcare: past, present and future
Fei Jiang, Yong Jiang, Hui Zhi, et al.
Stroke and Vascular Neurology (2017) Vol. 2, Iss. 4, pp. 230-243
Open Access | Times Cited: 3275
Deep Learning in Mobile and Wireless Networking: A Survey
Chaoyun Zhang, Paul Patras, Hamed Haddadi
IEEE Communications Surveys & Tutorials (2019) Vol. 21, Iss. 3, pp. 2224-2287
Open Access | Times Cited: 1498
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
Mehdi Mohammadi, Ala Al‐Fuqaha, Sameh Sorour, et al.
IEEE Communications Surveys & Tutorials (2018) Vol. 20, Iss. 4, pp. 2923-2960
Open Access | Times Cited: 1258
An overview of deep learning in medical imaging focusing on MRI
Alexander Selvikvåg Lundervold, Arvid Lundervold
Zeitschrift für Medizinische Physik (2018) Vol. 29, Iss. 2, pp. 102-127
Open Access | Times Cited: 980
Classification using deep learning neural networks for brain tumors
Heba Mohsen, El‐Sayed A. El‐Dahshan, El-Sayed M. El-Horbaty, et al.
Future Computing and Informatics Journal (2017) Vol. 3, Iss. 1, pp. 68-71
Open Access | Times Cited: 911
Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals
U. Rajendra Acharya, Hamido Fujita, Shu Lih Oh, et al.
Information Sciences (2017) Vol. 415-416, pp. 190-198
Closed Access | Times Cited: 844
Applications of Deep Learning and Reinforcement Learning to Biological Data
Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, et al.
IEEE Transactions on Neural Networks and Learning Systems (2018) Vol. 29, Iss. 6, pp. 2063-2079
Open Access | Times Cited: 777
Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Henry Friday Nweke, Teh Ying Wah, Mohammed Ali Al-Garadi, et al.
Expert Systems with Applications (2018) Vol. 105, pp. 233-261
Closed Access | Times Cited: 776
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis
Benjamin Shickel, Patrick J. Tighe, Azra Bihorac, et al.
IEEE Journal of Biomedical and Health Informatics (2017) Vol. 22, Iss. 5, pp. 1589-1604
Open Access | Times Cited: 731
Study on artificial intelligence: The state of the art and future prospects
Caiming Zhang, Yang Lu
Journal of Industrial Information Integration (2021) Vol. 23, pp. 100224-100224
Closed Access | Times Cited: 724
Frontiers in Artificial Intelligence and Applications
Jaya Yadav, Shruti Shukla, Kanika Sharma, et al.
(2022), pp. 1-6
Closed Access | Times Cited: 639
Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine
Filippo Pesapane, Marina Codari, Francesco Sardanelli
European Radiology Experimental (2018) Vol. 2, Iss. 1
Open Access | Times Cited: 637
Plant Disease Detection and Classification by Deep Learning
Muhammad Hammad Saleem, Johan Potgieter, Khalid Mahmood Arif
Plants (2019) Vol. 8, Iss. 11, pp. 468-468
Open Access | Times Cited: 614
Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success
James H. Thrall, Xiang Li, Quanzheng Li, et al.
Journal of the American College of Radiology (2018) Vol. 15, Iss. 3, pp. 504-508
Closed Access | Times Cited: 610
Convolutional neural networks in medical image understanding: a survey
D. R. Sarvamangala, Raghavendra V. Kulkarni
Evolutionary Intelligence (2021) Vol. 15, Iss. 1, pp. 1-22
Open Access | Times Cited: 575
A Review of Machine Learning and Deep Learning Applications
Pramila Shinde, Seema Shah
(2018), pp. 1-6
Closed Access | Times Cited: 543
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis
Davood Karimi, Haoran Dou, Simon K. Warfield, et al.
Medical Image Analysis (2020) Vol. 65, pp. 101759-101759
Open Access | Times Cited: 522
The importance of interpretability and visualization in machine learning for applications in medicine and health care
Alfredo Vellido
Neural Computing and Applications (2019) Vol. 32, Iss. 24, pp. 18069-18083
Closed Access | Times Cited: 468
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
Monika A. Myszczynska, Poojitha N. Ojamies, Alix M.B. Lacoste, et al.
Nature Reviews Neurology (2020) Vol. 16, Iss. 8, pp. 440-456
Closed Access | Times Cited: 435
Deep Learning and Medical Diagnosis: A Review of Literature
Mihalj Bakator, Dragica Radosav
Multimodal Technologies and Interaction (2018) Vol. 2, Iss. 3, pp. 47-47
Open Access | Times Cited: 425
A review on deep learning in medical image analysis
S. Suganyadevi, V. Seethalakshmi, K. Balasamy
International Journal of Multimedia Information Retrieval (2021) Vol. 11, Iss. 1, pp. 19-38
Open Access | Times Cited: 375
Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States
Filippo Pesapane, Caterina Volonté, Marina Codari, et al.
Insights into Imaging (2018) Vol. 9, Iss. 5, pp. 745-753
Open Access | Times Cited: 364
Deep Learning in Mining Biological Data
Mufti Mahmud, M. Shamim Kaiser, T.M. McGinnity, et al.
Cognitive Computation (2021) Vol. 13, Iss. 1, pp. 1-33
Open Access | Times Cited: 352
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study
Zhibin Zhao, Qiyang Zhang, Xiaolei Yu, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-28
Open Access | Times Cited: 332
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