instruction:
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".
question:
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
answer:
False


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Paragraph: Feedback from operational stakeholders who manage or respond to outbreaks is that they are often too busy to review literature or obtain relevant background information to assist them with acute response. Unlike a traditional analytical outbreak investigation report, Watching Briefs are intended as a rapid resource for public health or other first responders in the field on topical, serious or current outbreaks, and provide a digest of relevant information including key features of an outbreak, comparison with past outbreaks and a literature review. They can be completed by responders to an outbreak, or by anyone interested in or following an outbreak using public or open source data, including news reports. 
 Title: Watching brief Title Wuhan novel coronavirus 2019nCoV
answer:
False


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Paragraph: Hepatitis C affects about 3% of the world population, yet its current treatment options are limited to interferon-ribavirin drug regimens which achieve a 50-70% cure rate depending on the hepatitis C virus (HCV) genotype. Besides extensive screening for HCV-specific compounds, some wellestablished medicinal drugs have recently demonstrated anti-HCV effect in HCV replicon cells. One of these drugs is arbidol (ARB), a Russian-made broad spectrum antiviral agent, which we have previously shown to inhibit acute and chronic HCV infection. Here we show that ARB inhibits the cell entry of HCV pseudoparticles of genotypes 1a, 1b and 2a in a dose-dependent fashion. ARB also displayed a dose-dependent inhibition of HCV membrane fusion, as assayed by using HCV pseudoparticles (HCVpp) and fluorescent liposomes. ARB inhibition of HCVpp fusion was found more effective on genotype 1a than on genotypes 1b and 2a. In vitro biochemical studies revealed ARB association with membrane-like environments such as detergents, and with lipid membranes. This association was particularly prominent at acidic pH which is optimal for HCV-mediated fusion. Our results suggest that the affinity of ARB for lipid membranes could account for its anti-HCV actions, together with a differential level of interaction with key motifs in HCV glycoproteins of different genotypes. The hepatitis C virus (HCV) infects an estimated 3% or 170 million of the world's population, and hepatitis C is now the most frequent indication for liver transplantation. Current treatment options are limited to pegylated recombinant interferon alpha (IFN-α) in combination with ribavirin. However viremia eradication is variably achieved depending on the genotype, with only 50% of virus eradication in genotype 1-infected patients. This is clearly a problem in North America, Europe and Japan, where genotype 1 is the most prevalent genotype. HCV † This work was supported by the ANRS (Agence Nationale de Recherches sur le SIDA et les hepatites virales) to E.I.P. 
 Title: Biochemical mechanism of hepatitis C virus inhibition by the broad-spectrum antiviral arbidol † NIH Public Access Author Manuscript
answer:

True