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".

Example Input: Paragraph: Objective: The aim of this study was to further clarify clinical characteristics and predict mortality risk among patients with viral pneumonia. Methods: A total of 528 patients with viral pneumonia at RuiJin hospital in Shanghai from May 2015 to May 2019 were recruited. Multiplex real-time RT-PCR was used to detect respiratory viruses. Demographic information, comorbidities, routine laboratory examinations, immunological indexes, etiological detections, radiological images and treatment were collected on admission. Results: 76 (14.4%) patients died within 90 days in hospital. A predictive MuLBSTA score was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included multilobular infiltrates (OR = 5.20, 95% CI 1.41-12.52, p = 0.010; 5 points), lymphocyte ≤ 0.8 * 10 9 /L (OR = 4.53, 95% CI 2.55-8.05, p < 0.001; 4 points), bacterial coinfection (OR = 3.71, 95% CI 2.11-6.51, p < 0.001; 4 points), acute-smoker (OR = 3.19, 95% CI 1.34-6.26, p = 0.001; 3 points), quit-smoker (OR = 2.18, 95% CI 0.99-4.82, p = 0.054; 2 points), hypertension (OR = 2.39, 95% CI 1.55-4.26, p = 0.003; 2 points) and age ≥60 years (OR = 2.14, 95% CI 1.04-4.39, p = 0.038; 2 points). 12 points was used as a cut-off value for mortality risk stratification. This model showed sensitivity of 0.776, specificity of 0.778 and a better predictive ability than CURB-65 (AUROC = 0.773 vs. 0.717, p < 0.001). Conclusion: Here, we designed an easy-to-use clinically predictive tool for assessing 90-day mortality risk of viral pneumonia. It can accurately stratify hospitalized patients with viral pneumonia into relevant risk categories and could provide guidance to make further clinical decisions. 
 Title: Citation: Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score
Example Output: False

Example Input: Paragraph: A novel binding site for angiotensins II and III that is unmasked by parachloromercuribenzoate has been reported in rat, mouse and human brains. Initial studies of this binding site indicate that it is not expressed in the adrenal, liver or kidney of the rat and mouse. To determine if this binding site occurs in other mouse tissues, 8 tissues were assayed for expression of this binding site by radioligand binding assay and compared with the expression of this binding site in the forebrain. Particulate fractions of homogenates of testis, epididymis, seminal vesicles, heart, spleen, pancreas, lung, skeletal muscle, and forebrain were incubated with 125 I-sarcosine 1 , isoleucine 8 angiotensin II in the presence or absence of 0.3 mM parachloromercuribenzoate plus 10 µM losartan and 10 µM PD123319 (to saturate AT 1 and AT 2 receptors). Specific (3 µM angiotensin II displaceable) high affinity binding occurred in the testis N forebrainN epididymisN spleen N pancreas N lung when parachloromercuribenzoate was present. Binding could not be reliably observed in heart, skeletal muscle and seminal vesicles. High affinity binding of 125 I-sarcosine 1 , isoleucine 8 angiotensin II was observed in the absence of parachloromercuribenzoate in the pancreas on occasion. This suggests that this novel angiotensin binding site may have a functional role in these tissues. 
 Title: Distribution of a novel binding site for angiotensins II and III in mouse tissues
Example Output: False

Example Input: Paragraph: Objective: This study presents a preliminary report on the chest radiographic and computed tomography (CT) findings of the 2019 novel coronavirus disease (COVID-19) pneumonia in Korea. Materials and Methods: As part of a multi-institutional collaboration coordinated by the Korean Society of Thoracic Radiology, we collected nine patients with COVID-19 infections who had undergone chest radiography and CT scans. We analyzed the radiographic and CT findings of COVID-19 pneumonia at baseline. Fisher's exact test was used to compare CT findings depending on the shape of pulmonary lesions. Results: Three of the nine patients (33.3%) had parenchymal abnormalities detected by chest radiography, and most of the abnormalities were peripheral consolidations. Chest CT images showed bilateral involvement in eight of the nine patients, and a unilobar reversed halo sign in the other patient. In total, 77 pulmonary lesions were found, including patchy lesions (39%), large confluent lesions (13%), and small nodular lesions (48%). The peripheral and posterior lung fields were involved in 78% and 67% of the lesions, respectively. The lesions were typically ill-defined and were composed of mixed ground-glass opacities and consolidation or pure ground-glass opacities. Patchy to confluent lesions were primarily distributed in the lower lobes (p = 0.040) and along the pleura (p < 0.001), whereas nodular lesions were primarily distributed along the bronchovascular bundles (p = 0.006). Conclusion: COVID-19 pneumonia in Korea primarily manifested as pure to mixed ground-glass opacities with a patchy to confluent or nodular shape in the bilateral peripheral posterior lungs. A considerable proportion of patients with COVID-19 pneumonia had normal chest radiographs. 
 Title: Chest Radiographic and CT Findings of the 2019 Novel Coronavirus Disease (COVID-19): Analysis of Nine Patients Treated in Korea
Example Output:
True