Definition: In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
Input: Background: To control the spread of Corona Virus Disease , 30 screening large numbers of suspected cases for appropriate quarantine and 31 treatment is a priority. Pathogenic laboratory testing is the diagnostic gold standard 32 but it is time consuming with significant false negative results. Fast and accurate 33 diagnostic methods are urgently needed to combat the disease. Based on 34 COVID-19 radiographical changes in CT images, we aimed to develop a deep 35 learning method that could extract COVID-19's graphical features in order to provide 36 a clinical diagnosis ahead of the pathogenic test, thus saving critical time for 37 disease control. 38 Methods and Findings: We collected 1,065CT images of pathogen-confirmed 39 COVID-19 cases (325 images) along with those previously diagnosed with typical 40 viral pneumonia (740 images). We modified the Inception transfer-learning model 41 to establish the algorithm, followed by internal and external validation. The internal 42 validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity 43 of 0.87. The external testing dataset showed a total accuracy of 79.3% with 44 specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images that 45 first two nucleic acid test results were negative, 46 were predicted as COVID-19 46 positive by the algorithm, with the accuracy of 85.2%. 47 Conclusion: These results demonstrate the proof-of-principle for using 48 artificial intelligence to extract radiological features for timely and accurate 49 COVID-19 diagnosis. 50

Breast Cancer Prevention and Therapy, Ministry of Education