| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T1 |
0-104 |
Sentence |
denotes |
The importance of standardisation - COVID-19 CT & Radiograph Image Data Stock for deep learning purpose. |
| T2 |
105-222 |
Sentence |
denotes |
With the number of affected individuals still growing world-wide, the research on COVID-19 is continuously expanding. |
| T3 |
223-398 |
Sentence |
denotes |
The deep learning community concentrates their efforts on exploring if neural networks can potentially support the diagnosis using CT and radiograph images of patients' lungs. |
| T4 |
399-524 |
Sentence |
denotes |
The two most popular publicly available datasets for COVID-19 classification are COVID-CT and COVID-19 Image Data Collection. |
| T5 |
525-620 |
Sentence |
denotes |
In this work, we propose a new dataset which we call COVID-19 CT & Radiograph Image Data Stock. |
| T6 |
621-796 |
Sentence |
denotes |
It contains both CT and radiograph samples of COVID-19 lung findings and combines them with additional data to ensure a sufficient number of diverse COVID-19-negative samples. |
| T7 |
797-857 |
Sentence |
denotes |
Moreover, it is supplemented with a carefully defined split. |
| T8 |
858-1090 |
Sentence |
denotes |
The aim of COVID-19 CT & Radiograph Image Data Stock is to create a public pool of CT and radiograph images of lungs to increase the efficiency of distinguishing COVID-19 disease from other types of pneumonia and from healthy chest. |
| T9 |
1091-1294 |
Sentence |
denotes |
We hope that the creation of this dataset would allow standardisation of the approach taken for training deep neural networks for COVID-19 classification and eventually for building more reliable models. |
