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: Lower respiratory tract infections in the first years of life are associated with later asthma, and this observation has led to a focus on the potential causal role of specific respiratory viruses, such as rhinoviruses and respiratory syncytial virus, in asthma development. However, many respiratory viruses and bacteria trigger similar respiratory symptoms and it is possible that the important risk factors for asthma are the underlying susceptibility to infection and the exaggerated reaction to such triggers rather than the particular triggering agent. Objective: We sought to study the association between specific infections in early life and development of asthma later in childhood. Methods: Three hundred thirteen children were followed prospectively in the Copenhagen Prospective Studies of Asthma in Childhood 2000 high-risk birth cohort. Nine respiratory virus types (respiratory syncytial virus, rhinoviruses, other picornaviruses, coronaviruses 229E and OC43, parainfluenza viruses 1-3, influenza viruses AH1, AH3, and B, human metapneumovirus, adenoviruses, and bocavirus) and 3 pathogenic airway bacteria (Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis) were identified in airway secretions sampled during episodes of troublesome lung symptoms in the first 3 years of life. Asthma was determined by age 7 years. Results: In unadjusted analyses, all viruses and pathogenic bacteria identified during episodes of troublesome lung symptoms were associated with increased risk of asthma by age 7 years with similar odds ratios for all viruses and pathogenic bacteria. After adjustment for the frequency of respiratory episodes, the particular triggers were no longer associated with asthma. Conclusion: The number of respiratory episodes in the first years of life, but not the particular viral trigger, was associated with later asthma development. This suggests that future research should focus on the susceptibility and exaggerated response to lower respiratory tract infections in general rather than on the specific triggering agent. (J Allergy Clin Immunol 2015;136:81-6.)
[A]: Association between respiratory infections in early life and later asthma is independent of virus type


[Q]: Graphical Abstract Highlights d Catalytic site mutations were introduced in vaccinia virus decapping enzymes, D9 and D10 d D9 and D10 catalytic mutant virus exhibits replication defects and attenuation in mice d Mutant virus increases dsRNA, activates RNase L, and induces PKR phosphorylation d Protein synthesis is inhibited and RNA degraded in absence of functional D9 and D10 SUMMARY Poxvirus replication involves synthesis of doublestranded RNA (dsRNA), which can trigger antiviral responses by inducing phosphorylation-mediated activation of protein kinase R (PKR) and stimulating 2 0 5 0 -oligoadenylate synthetase (OAS). PKR inactivates the translation initiation factor eIF2a via phosphorylation, while OAS induces the endonuclease RNase L to degrade RNA. We show that poxvirus decapping enzymes D9 and D10, which remove caps from mRNAs, inhibit these antiviral responses by preventing dsRNA accumulation. Catalytic site mutations of D9 and D10, but not of either enzyme alone, halt vaccinia virus late protein synthesis and inhibit virus replication. Infection with the D9-D10 mutant was accompanied by massive mRNA reduction, cleavage of ribosomal RNA, and phosphorylation of PKR and eIF2a that correlated with a 15-fold increase in dsRNA compared to wild-type virus. Additionally, mouse studies show extreme attenuation of the mutant virus. Thus, vaccinia virus decapping, in addition to targeting mRNAs for degradation, prevents dsRNA accumulation and anti-viral responses.
[A]:
Poxvirus Decapping Enzymes Enhance Virulence by Preventing the Accumulation of dsRNA and the Induction of Innate Antiviral Responses Article Poxvirus Decapping Enzymes Enhance Virulence by Preventing the Accumulation of dsRNA and the Induction of Innate Antiviral Responses