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Mendeley readers
Title |
COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography
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Published in |
Frontiers in Artificial Intelligence, June 2024
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DOI | 10.3389/frai.2024.1304483 |
Pubmed ID | |
Authors |
Sushant Agarwal, Sanjay Saxena, Alessandro Carriero, Gian Luca Chabert, Gobinath Ravindran, Sudip Paul, John R. Laird, Deepak Garg, Mostafa Fatemi, Lopamudra Mohanty, Arun K. Dubey, Rajesh Singh, Mostafa M. Fouda, Narpinder Singh, Subbaram Naidu, Klaudija Viskovic, Melita Kukuljan, Manudeep K. Kalra, Luca Saba, Jasjit S. Suri |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 3 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Unspecified | 2 | 67% |
Lecturer | 1 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Unspecified | 2 | 67% |
Business, Management and Accounting | 1 | 33% |