Table 4.
Summary of papers for COVID-19 detection using deep learning.
| Authors | Deep Learning Technique | Features | Dataset |
|---|---|---|---|
| [137] | CNN with transfer learning and location-attention classification mechanism | Features extracted from CNN | Private dataset |
| [125] | CNN with transfer learning and data augmentation | Features extracted from CNN | SIRM database, Cohen’s Github dataset, Chowdhury’s Kaggle dataset |
| [26] | RADLogics Inc., CNN with transfer learning and data augmentation | Features extracted from RADLogics Inc and CNN | Chainz Dataset, A dataset from a hospital in Wenzhou, China, Dataset from El-Camino Hospital (CA) and Lung image database consortium (LIDC) |
| [123] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github dataset and LDOCTCXR |
| [21] | CNN with transfer learning and data augmentation | Features extracted from CNN | Cohen’s Github dataset and unspecified Kaggle dataset |
| [135] | VB-Net and modified random decision forests method | 96 handcrafted image features | Dataset obtained from Tongji Hospital of Huazhong University of Science and Technology, Shanghai Public Health Clinical Center of Fudan University, and China-Japan Union Hospital of Jilin University. |
| [126] | CNN from scratch and data augmentation | Features extracted from CNN | COVIDx Dataset |
| [127] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github dataset, Andrew’s Kaggle dataset, LDOCTCXR |
| [117] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github dataset, RSNA pneumonia dataset, COVIDx |
| [131] | CNN with transfer learning and data augmentation | Features extracted from CNN | Sajid’s Kaggle dataset |
| [4] | CNN with transfer learning and data augmentation | Features extracted from CNN | Cohen’s Github dataset, Mooney’s Kaggle dataset |
| [118] | CNN with transfer learning | Features extracted from CNN | COVID-CT-Dataset |
| [128] | CNN as feature extractor and long short-term memory (LSTM) network as classifier | Features extracted from CNN | GitHub, Radiopaedia, The Cancer Imaging Archive, SIRM, Kaggle repository, NIH dataset, Mendeley dataset |
| [132] | CNN with transfer learning and synthetic data generation and augmentation | Features extracted from CNN | Cohen’s Github, Chowdhury’s Kaggle dataset, COVID-19 Chest X-ray Dataset, Initiative |
| [129] | CNN with transfer learning, data augmentation and ensemble by majority voting | Features extracted from CNN | Cohen’s Github, LDOCTCXR |
| [134] | CNN with transfer learning and stacking ensemble | Features extracted from CNN | Private dataset, LDOCTCXR |
| [130] | CNN | Features extracted from CNN | Private dataset |
| [138] | Multi-objective differential evolution-based CNN | Features extracted from CNN | Unspecified |
| [119] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github |
| [139] | CNN and ConvLSTM with data augmentation | Features extracted from CNN | Cohen’s Github, COVID-CT-Dataset |
| [120] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github |
| [133] | CNN with ensemble by weighted averaging | Features extracted from CNN | Private hospital datasets |
| [121] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github, Mooney’s Kaggle dataset, Shenzhen and Montgomery datasets |
| [140] | MLP-CNN based model | Features extracted from CNN | Cohen’s Github |
| [122] | CNN with transfer learning | Features extracted from CNN | Cohen’s Github, unspecified Kaggle dataset |
| [141] | Capsule Network-based framework with transfer learning | Features extracted from CNN | Cohen’s Github, Mooney’s Kaggle dataset |