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: Surveillance is essential to estimating the global burden of pneumonia, yet differences in surveillance methodology and health care-seeking behaviors limit inter-country comparisons. Methods: Results were compared from community surveys measuring health care-seeking for pneumonia defined as: (1) cough and difficulty breathing for P2 days; or, (2) provider-diagnosed pneumonia. Surveys were conducted in six sites in Guatemala, Kenya and Thailand; these sites also conduct, active, hospital-and population-based disease surveillance for pneumonia. Results: Frequency of self-reported pneumonia during the preceding year ranged from 1.1% (Thailand) to 6.3% (Guatemala) and was highest in children aged <5 years and in urban sites. The proportion of persons with pneumonia who sought hospitalbased medical services ranged from 12% (Guatemala, Kenya) to 80% (Thailand) and was highest in children <5 years of age. Hospitals and private provider offices were the most common places where persons with pneumonia sought health care. The most commonly cited reasons for not seeking health care were: (a) mild illness; (b) already recovering; and (3) cost of treatment. Conclusions: Health care-seeking patterns varied widely across countries. Using results from standardized health care utilization surveys to adjust facility-based surveillance estimates of pneumonia allows for more accurate and comparable estimates.
[A]: Putting surveillance data into context: The role of health care utilization surveys in understanding population burden of pneumonia in developing countries


[Q]: Epidemiologic investigations showed that 2 of 4 patients with severe acute respiratory syndrome (SARS) identified in the winter of 2003-2004 were a waitress at a restaurant in Guangzhou, China, that served palm civets as food and a customer who ate in the restaurant a short distance from animal cages. All 6 palm civets at the restaurant were positive for SARS-associated coronavirus (SARS-CoV). Partial spike (S) gene sequences of SARS-CoV from the 2 patients were identical to 4 of 5 S gene viral sequences from palm civets. Phylogenetic analysis showed that SARS-CoV from palm civets in the restaurant was most closely related to animal isolates. SARS cases at the restaurant were the result of recent interspecies transfer from the putative palm civet reservoir, and not the result of continued circulation of SARS-CoV in the human population.
[A]:
SARS-CoV Infection in a Restaurant from Palm Civet SARS-CoV Infection in a Restaurant from Palm Civet Emerging Infectious Diseases • www Past Issues on SARS


