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.
--------
Question: 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.

Answer: 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


Question: Ca 2+ is one of the most universal and versatile signaling molecules and is involved in almost every aspect of cellular processes. Viruses are adept at utilizing the universal Ca 2+ signal to create a tailored cellular environment that meets their own demands. This review summarizes most of the known mechanisms by which viruses perturb Ca 2+ homeostasis and utilize Ca 2+ and cellular Ca 2+ -binding proteins to their benefit in their replication cycles. Ca 2+ plays important roles in virion structure formation, virus entry, viral gene expression, posttranslational processing of viral proteins and virion maturation and release. As part of the review, we introduce an algorithm to identify linear "EF-hand" Ca 2+ -binding motifs which resulted in the prediction of a total of 93 previously unrecognized Ca 2+ -binding motifs in virus proteins. Many of these proteins are nonstructural proteins, a class of proteins among which Ca 2+ interactions had not been formerly appreciated. The presence of linear Ca 2+ -binding motifs in viral proteins enlarges the spectrum of Ca 2+ -virus interplay and expands the total scenario of viral calciomics. (J.J. Yang). for structural integrity or functionality; and (3) critical virus-host interactions depend on cellular Ca 2+ -regulated proteins or pathways. This review, which aims to stimulate future studies on the roles of Ca 2+ in virus infection, is focused on such interplay by highlighting recent discoveries in the biological roles of Ca 2+ in virus infection. 0143-4160/$ -see front matter

Answer: Viral calciomics: Interplays between Ca 2+ and virus


Question: Background: Nucleoli are composed of possibly several thousand different proteins and represent the most conspicuous compartments in the nucleus; they play a crucial role in the proper execution of many cellular processes. As such, nucleoli carry out ribosome biogenesis and sequester or associate with key molecules that regulate cell cycle progression, tumorigenesis, apoptosis and the stress response. Nucleoli are dynamic compartments that are characterized by a constant flux of macromolecules. Given the complex and dynamic composition of the nucleolar proteome, it is challenging to link modifications in nucleolar composition to downstream effects. Results: In this contribution, we present quantitative immunofluorescence methods that rely on computer-based image analysis. We demonstrate the effectiveness of these techniques by monitoring the dynamic association of proteins and RNA with nucleoli under different physiological conditions. Thus, the protocols described by us were employed to study stress-dependent changes in the nucleolar concentration of endogenous and GFP-tagged proteins. Furthermore, our methods were applied to measure de novo RNA synthesis that is associated with nucleoli. We show that the techniques described here can be easily combined with automated high throughput screening (HTS) platforms, making it possible to obtain large data sets and analyze many of the biological processes that are located in nucleoli. Conclusions: Our protocols set the stage to analyze in a quantitative fashion the kinetics of shuttling nucleolar proteins, both at the single cell level as well as for a large number of cells. Moreover, the procedures described here are compatible with high throughput image acquisition and analysis using HTS automated platforms, thereby providing the basis to quantify nucleolar components and activities for numerous samples and experimental conditions. Together with the growing amount of information obtained for the nucleolar proteome, improvements in quantitative microscopy as they are described here can be expected to produce new insights into the complex biological functions that are orchestrated by the nucleolus.

Answer:
Computer-based fluorescence quantification: a novel approach to study nucleolar biology