TASK DEFINITION: In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".
PROBLEM: Paragraph: 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. 
 Title: 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

SOLUTION: False

PROBLEM: Paragraph: Background: Embryonated chicken eggs have been used since the mid-20th century to grow a wide range of animal viruses to high titers. However, eggs have found so far only limited use in the production of recombinant proteins. We now describe a system, based on a Sendai virus minigenome, to produce large amounts of heterologous viral glycoproteins in the allantoic cavity of embryonated eggs. Results: Soluble forms of human respiratory syncytial virus (HRSV) and human metapneumovirus (HMPV) fusion (F) proteins, devoid of their transmembrane and cytoplasmic domains, were produced in allantoic fluids using the Sendai minigenome system. The first step was rescuing in cell cultures Sendai virus minigenomes encoding the proteins of interest, with the help of wild type Sendai virus. The second step was propagating such recombinant defective viruses, together with the helper virus, in the allantoic cavity of chicken embryonated eggs, and passage to optimize protein production. When compared with the production of the same proteins in the culture supernatant of cells infected with vaccinia recombinants, the yield in the allantoic fluid was 5-10 fold higher. Mutant forms of these soluble proteins were easily constructed by site-directed mutagenesis and expressed in eggs using the same approach. The simplicity and economy of the Sendai minigenome system, together with the high yield achieved in the allantoic fluid of eggs, makes it an attractive method to express soluble glycoproteins aimed for structural studies. 
 Title: High level expression of soluble glycoproteins in the allantoic fluid of embryonated chicken eggs using a Sendai virus minigenome system

SOLUTION: True

PROBLEM: Paragraph: respiratory symptoms in adults in general practice. Family Practice 2004; 21: 317-323. Background. Community studies have shown that ~30% of patients with acute respiratory tract symptoms have no identifiable infective aetiology. This may not be applicable in general practice. Objective. The purpose of this study was to determine the infective aetiology in patients who presented to primary care doctors with acute respiratory symptoms. Methods. A prospective study was carried out in all nine primary care clinics belonging to the National Healthcare Group Polyclinics (NHGPs) in Singapore. The subjects comprised 594 consecutive patients (318 males, 276 females) aged у21 years who presented with complaints of any one of cough, nasal or throat symptoms of Ͻ7 days duration. Data collection was through interview using structured questionnaire, physical examination, throat swabs for bacterial culture and nasal swabs for virus identification by immunofluorescence (IF) and polymerase chain reaction (PCR). Additional PCR was performed on a subsample of 100 patients. Patients were followed-up until resolution of symptoms. Results. The aetiological diagnosis by infective agent is as follows: 150 patients (25.2%) had virus infections, of which 90.7% (136/150) were by rhinovirus. Fourteen patients (2.4%) had bacterial infections, of which 10 were due to group G streptococcus. Group A streptococcus was not detected. Nineteen patients with new pathogens were identified by further PCR. These included parainfluenza 4, human coronavirus OC43, adenovirus, enterovirus and Chlamydia pneumoniae. No pathogen could be identified in 49% of patients. There were no differences in clinical presentation and socio-demographic variables between patients who had viral infections and those in whom no pathogen could be identified. In about half of patients who presented at NHGPs, no pathogens could be identified even after PCR. A non-infective aetiology could be considered in these patients. 
 Title: Acute respiratory symptoms in adults in general practice

SOLUTION:
False