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: Although coronavirus tropism is most often ascribed to receptor availability, increasing evidence suggests that for the neurotropic strains of the murine coronavirus mouse hepatitis virus (MHV), spike-receptor interactions cannot fully explain neurovirulence. The canonical MHV receptor CEACAM1a and its spike-binding site have been extensively characterized. However, CEACAM1a is poorly expressed in neurons, and the extremely neurotropic MHV strain JHM.SD infects ceacam1a S/S mice and spreads among ceacam1a S/S neurons. Two proposed alternative MHV receptors, CEACAM2 and PSG16, also fail to account for neuronal spread of JHM.SD in the absence of CEACAM1a. It has been reported that JHM.SD has an unusually labile spike protein, enabling it to perform receptor-independent spread (RIS), but it is not clear if the ability to perform RIS is fully responsible for the extremely neurovirulent phenotype. We propose that the extreme neurovirulence of JHM.SD is multifactorial and might include as yet unidentified neuron-specific spread mechanisms. 
 Title: Pathogenesis of neurotropic murine coronavirus is multifactorial
Example Output: True

Example Input: Paragraph: Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time. 
 Title: Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol
Example Output: True

Example Input: Paragraph: Seasonal hyperacute panuveitis (SHAPU) is a potentially blinding ocular disease occurring in Nepal that principally affects young children. Random amplification of partially purified vitreous fluid (VF)-derived nucleic acid revealed the presence of human anelloviruses in VF of SHAPU patients. In a comparative study of patients with different ocular pathologies, SHAPU patients were at highest risk of harboring anelloviruses in their eyes. The majority of SHAPU patients had multiple anelloviruses in their VF. The ocular anellovirus load in SHAPU and non-SHAPU patients did not differ and no SHAPU-specific anellovirus variant was detected. Analysis of paired serum and VF samples from SHAPU and non-SHAPU patients showed that the anellovirus detected in VF samples most likely originated from the systemic viral pool during viremia, potentially through breakdown of the blood-ocular barrier. The detection of anelloviruses in VF samples of uveitis patients, profoundly so in SHAPU patients, is imperative and warrants elucidation of its clinical significance. 
 Title: High Prevalence of Anelloviruses in Vitreous Fluid of Children With Seasonal Hyperacute Panuveitis
Example Output:
True