| 1 |
[GO] |
2025―Feb―26 |
Explained Deep Learning Framework for COVID-19 Detection in Volumetric CT Images Aligned with the British Society of Thoracic Imaging Reporting Guidance: A Pilot Study |
Shereen Fouad, Muhammad Usman, Ra’eesa Kabir, Arvind Rajasekaran, John Morlese, Pankaj Nagori, Bahadar Bhatia |
| 2 |
[GO] |
2025―Jan―23 |
Unlocking the Power of 3D Convolutional Neural Networks for COVID-19 Detection: A Comprehensive Review |
Ademola E. Ilesanmi, Taiwo Ilesanmi, Babatunde Ajayi, Gbenga A. Gbotoso, Samir Brahim Belhaouari |
| 3 |
[GO] |
2024―Mrz―18 |
Automated Detection of COVID-19 from Multimodal Imaging Data Using Optimized Convolutional Neural Network Model |
S. Veluchamy, S. Sudharson, R. Annamalai, Zaid Bassfar, Amer Aljaedi, Sajjad Shaukat Jamal |
| 4 |
[GO] |
2024―Feb―21 |
DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification |
Dina A. Ragab, Salema Fayed, Noha Ghatwary |
| 5 |
[GO] |
2024―Feb―13 |
Synthesis of Hybrid Data Consisting of Chest Radiographs and Tabular Clinical Records Using Dual Generative Models for COVID-19 Positive Cases |
Tomohiro Kikuchi, Shouhei Hanaoka, Takahiro Nakao, Tomomi Takenaga, Yukihiro Nomura, Harushi Mori, Takeharu Yoshikawa |
| 6 |
[GO] |
2024―Jan―12 |
Using the Textual Content of Radiological Reports to Detect Emerging Diseases: A Proof-of-Concept Study of COVID-19 |
Amandine Crombé, Jean-Christophe Lecomte, Mylène Seux, Nathan Banaste, Guillaume Gorincour |
