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".

Ex 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

Ex Output:
True

Ex Input:
Paragraph: Introduction-HIV-1 uses a programmed -1 ribosomal frameshift to generate Gag-Pol, the precursor of its enzymes, when its full-length mRNA is translated by the ribosomes of the infected cells. This change in the reading frame occurs at a so-called slippery sequence that is followed by a specific secondary structure, the frameshift stimulatory signal. This signal controls the frameshift efficiency. The synthesis of HIV-1 enzymes is critical for the virus replication and therefore, the -1 ribosomal frameshift could be the target of novel antiviral drugs. Areas covered-This review examines various approaches used to select drugs interfering with the -1 frameshift of HIV-1. These include the selection and modification of chemical compounds that specifically bind to the frameshift stimulatory signal, the use of antisense oligonucleotides targeting this signal and the selection of compounds that modulate HIV-1 frameshift, by using bicistronic reporters where the expression of the second cistron depends upon HIV-1 frameshift. Expert opinion-The most promising approach is the selection and modification of compounds specifically targeting HIV-1 frameshift stimulatory signal. The use of antisense oligonucleotides binding to the frameshift stimulatory signal is still questionable. The use of bicistronic reporters preferentially selects compounds that modulate the frameshift by targeting the ribosomes, which is less promising.
Title: Targeting frameshifting in the human immunodeficiency virus

Ex Output:
True

Ex Input:
Paragraph: The main peptidase (M pro ) from the coronavirus (CoV) causing severe acute respiratory syndrome (SARS) is one of the most attractive molecular targets for the development of anti-SARS agents. We report the irreversible inhibition of SARS-CoV M pro by an aza-peptide epoxide (APE; k inact /K i Z 1900(G400) M K1 s K1 ). The crystal structures of the M pro :APE complex in the space groups C2 and P2 1 2 1 2 1 revealed the formation of a covalent bond between the catalytic Cys145 S g atom of the peptidase and the epoxide C3 atom of the inhibitor, substantiating the mode of action of this class of cysteine-peptidase inhibitors. The aza-peptide component of APE binds in the substrate-binding regions of M pro in a substrate-like manner, with excellent structural and chemical complementarity. In addition, the crystal structure of unbound M pro in the space group C2 revealed that the "N-fingers" (N-terminal residues 1 to 7) of both protomers of M pro are well defined and the substrate-binding regions of both protomers are in the catalytically competent conformation at the crystallization pH of 6.5, contrary to the previously determined crystal structures of unbound M pro in the space group P2 1 .
Title: Crystal Structures of the Main Peptidase from the SARS Coronavirus Inhibited by a Substrate-like Aza-peptide Epoxide

Ex Output:
False