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.

Example Input: 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.
Example Output: 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

Example Input: After decades of low personal risk for contracting lethal diseases, physicians are suddenly facing the possibility of a substantial increase in occupational risk during an influenza pandemic. If they are not confronted before the onset of an influenza pandemic, feelings of unease and fear or ignorance about physicians' professional obligations could profoundly hinder individual physicians in fulfilling their professional duties. Such feelings could therefore undermine institutional and societal preparations. In their review published in Critical Care, Anantham and coworkers outline the ethical framework that forms the basis of the professional obligations of physicians who respond to health care emergencies, such as an influenza pandemic.
Example Output: Pandemic influenza: are we prepared to face our obligations?

Example Input: As a result of the efforts of the Human Genome Project and the rise in demand for molecular diagnostic assays, the development and optimization of novel hybridization probes have focused on speed, reliability, and accuracy in the identification of nucleic acids. Molecular beacons (MBs) are single-stranded, fluorophore-labeled nucleic acid probes that are capable of generating a fluorescent signal in the presence of target, but are dark in the absence of target. Because of the high specificity and sensitivity characteristics, MBs have been used in variety of fields. In this review, MBs are introduced and discussed as diagnostic tools in four sections: several technologies of MBs will be illustrated primarily; the limitation of MBs next; the third part is new fashions of MBs; and the last one is to present the application of MBs in disease diagnosis.
Example Output:
Molecular Beacons: A Novel Optical Diagnostic Tool