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 The aim of this study was to assess multiplex PCR analysis in detecting causative viruses in children with febrile seizures. Methods The study was a retrospective analysis comparing data from a pre-multiplex era (2009) with a period after the introduction of routine respiratory multiplex analysis (2010-2013) in children with febrile seizures. Results We included 200 children with febrile seizures (mean age: 29.5 ± 1.4.months; 104 male) in the study. In 2009, in 10 out of 49 (20 %) children, microbiology testing (bacterial/fungal) was positive compared with a rate of 74 out of 151 (49 %) children during 2010-2013 (p < 0.01). The rate of positive virological studies increased from 10 (20 %) in 2009 to 73 (48.3 %) in the period 2010-2013 (p < 0.01). Multiplex PCR analysis confirmed viral infections in 52 of 73 cases (71.2 %). Conclusion Routine multiplex PCR analysis fosters the detection of respiratory viruses in children with febrile seizure. The precise role of multiplex analysis in the J. 
 Title: Role of multiplex PCR analysis in children with febrile seizures management of these children awaits further clarifi- cation

SOLUTION: True

PROBLEM: Paragraph: We previously reported the crystal structure of an acetyl esterase (TcAE206) belonging to carbohydrate esterase family 3 from Talaromyces cellulolyticus. In this study, we solved the crystal structure of an S10A mutant of TcAE206 complexed with an acetate ion. The acetate ion was stabilized by three hydrogen bonds in the oxyanion hole instead of a water molecule as in the structure of wild-type TcAE206. Furthermore, the catalytic triad residue His182 moved 0.8 Å toward the acetate ion upon substrate entering the active site, suggesting that this movement is necessary for completion of the catalytic reaction. 
 Title: Crystal structure of an acetyl esterase complexed with acetate ion provides insights into the catalytic mechanism

SOLUTION:
False