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.

[Q]: Purpose: COVID-19 has become global threaten. CT acts as an important method of 60 diagnosis. However, human-based interpretation of CT imaging is time consuming. 61 More than that, substantial inter-observer-variation cannot be ignored. We aim at 62 developing a diagnostic tool for artificial intelligence (AI)-based classification of CT 63 images for recognizing COVID-19 and other common infectious diseases of the lung. 64 Experimental Design: In this study, images were retrospectively collected and 65 prospectively analyzed using machine learning. CT scan images of the lung that show 66 or do not show COVID-19 were used to train and validate a classification framework 67 based on convolutional neural network. Five conditions including COVID-19 68 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, pulmonary 69 tuberculosis, and normal lung were evaluated. Training and validation set of images 70 were collected from Wuhan Jin Yin-Tan Hospital whereas test set of images were 71 collected from Zhongshan Hospital Xiamen University and the fifth Hospital of 72 Wuhan. 73 Results: Accuracy, sensitivity, and specificity of the AI framework were reported. For 74 test dataset, accuracies for recognizing normal lung, COVID-19 pneumonia, 75 non-COVID-19 viral pneumonia, bacterial pneumonia, and pulmonary tuberculosis 76 were 99.4%, 98.8%, 98.5%, 98.3%, and 98.6%, respectively. For the test dataset, 77 accuracy, sensitivity, specificity, PPV, and NPV of recognizing COVID-19 were 78 98.8%, 98.2%, 98.9%, 94.5%, and 99.7%, respectively. 79 All rights reserved. No reuse allowed without permission. the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
[A]: Deep Learning-Based Recognizing COVID-19 Deep Learning-Based Recognizing COVID-19 and other Common Infectious Diseases of the Lung by Chest CT 2 Scan Images

[Q]: Background: Diagnosis of community-acquired pneumonia (CAP) caused by Mycoplasma pneumoniae (Mp) in children has been hampered by difficulty in obtaining convalescent serum and time constraints. In this study, the two diagnostic assays that targeted respectively on Mp-antibody and Mp-DNA were retrospectively investigated. Methods: A total of 3146 children were clinically diagnosed to have CAP and were confirmed by chest X-ray during March 2015 to February 2016 in Children's hospital of Hebei Province (China). Both of the sera and sputum samples were collected in 24 h after their admission. The Mp-antibody was examined by the passive particle agglutination assay and a fourfold or greater increase of antibody titers of paired sera or1:160 titer of single serum was set as the serology positive. Mp-DNA in the sputum samples was tested by a multiplex-PCR method named GeXP assay (multiplex PCR combined with automated capillary electrophoresis). In order to eliminate the false positive results caused by the asymptomatic carriage after infected by M. pneumoniae, the inconsistent samples were tested by the real-time isothermal transcription-mediated RNA amplification assay (SAT). The inter-rated agreement test was performed in 3146 CAP patients, with a highest kappa value in the schoolage children as 0.783. There were 6.29% (198/3146) cases showed inconsistent results determined by GeXP and serology assay. All of the 19 GeXP(+)/Serology () samples and a randomly chosen 27 from 179 GeXP()/Serology (+) samples were tested by SAT assay, and a 97.8% diagnosis agreement was observed between SAT and GeXP assay, but not with the serology assay. In addition, patients who were detected only by serology or only by multiplex-PCR were significantly younger than those with both methods positive (3.0 and 1.5 years vs. 5.0 years, p < 0. 01). The Viral-Mp coinfection accounted for 37.0% (97/262), which was more common in winter and spring (p < 0.05) and in the infantile group (p < 0.01), compared to the pure Mp positive ones. In some children CAP cases, the Mp laboratory diagnosis was inconsistent between serology and multiplex-PCR assay. Verified by the SAT assay, the GeXP showed a more sensitive and reliable performance compared with the serology assay. Furthermore, employing the multiplex-PCR could provide more information on the associated pathogens for clinical assessment of CAP.
[A]: A comparison study between GeXP-based multiplex-PCR and serology assay for Mycoplasma pneumoniae detection in children with community acquired pneumonia

[Q]: The laboratory diagnosis of dengue has largely relied on serological assays, although many different RT-PCR protocols have been reported. Owing to its limited use, the value of RT-PCR in the clinical laboratory has not been fully evaluated. During the outbreak of severe acute respiratory syndrome (SARS) in Singapore in 2003, RT-PCR to detect dengue viral RNA was used as a rapid diagnostic tool to differentiate dengue from SARS among patients who presented to a hospital designated to manage and quarantine SARS cases. A total of 343 results for RT-PCR and 439 results for serology were analysed and compared with the final discharge diagnosis. Our experience indicates that RT-PCR for dengue can be set up rapidly in a clinical laboratory, with very sensitive and specific results for the diagnosis of dengue, particularly in the first 5 days from onset of symptoms.
[A]:
The performance of RT-PCR compared with a rapid serological assay for acute dengue fever in a diagnostic laboratory