Editorial on Special Issue “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care”
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Published:2024-09-07
Issue:17
Volume:14
Page:1984
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ISSN:2075-4418
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Container-title:Diagnostics
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language:en
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Short-container-title:Diagnostics
Author:
Rajaraman Sivaramakrishnan1ORCID, Xue Zhiyun1, Antani Sameer1ORCID
Affiliation:
1. Computational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
Abstract
In an era of rapid advancements in artificial intelligence (AI) technologies, particularly in medical imaging and natural language processing, strategic efforts to leverage AI’s capabilities in analyzing complex medical data and integrating it into clinical workflows have emerged as a key driver of innovation in healthcare [...]
Funder
Intramural Research Program of the National Library of Medicine (NLM) at the National Institutes of Health
Reference19 articles.
1. A Guide to Deep Learning in Healthcare;Esteva;Nat. Med.,2019 2. Data Characterization for Reliable AI in Medicine;Rajaraman;Recent Trends in Image Processing and Pattern Recognition,2023 3. Ganesan, P., Rajaraman, S., Long, R., Ghoraani, B., and Antani, S. (2019, January 23–27). Assessment of Data Augmentation Strategies Toward Performance Improvement of Abnormality Classification in Chest Radiographs. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Berlin, Germany. 4. Ganesan, P., Feng, R., Deb, B., Tjong, F.V.Y., Rogers, A.J., Ruipérez-Campillo, S., Somani, S., Clopton, P., Baykaner, T., and Rodrigo, M. (2024). Novel Domain Knowledge-Encoding Algorithm Enables Label-Efficient Deep Learning for Cardiac CT Segmentation to Guide Atrial Fibrillation Treatment in a Pilot Dataset. Diagnostics, 14. 5. Kolhar, M., Kazi, R.N.A., Mohapatra, H., and Al Rajeh, A.M. (2024). AI-Driven Real-Time Classification of ECG Signals for Cardiac Monitoring Using i-AlexNet Architecture. Diagnostics, 14.
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