The Use of Machine Learning and Predictive Modelling Methods in the Identification of Hosts for Viral Infections: Scoping Review Protocol

dc.contributor.authorAlberts, Famke
dc.contributor.authorKeay, Sheila
dc.contributor.authorPoljak, Zvonimir
dc.date.accessioned2021-07-28T16:14:50Z
dc.date.available2021-07-28T16:14:50Z
dc.date.created2021-07-28
dc.degree.departmentDepartment of Population Medicineen
dc.description.abstractBackground: Advanced in-silico predictive modelling techniques combining methods of machine learning and bioinformatics have been applied to predict the reservoir of a virus and all hosts that exist within that reservoir. However, a systematic compilation of this body of research does not exist. Objectives: This protocol describes the methods that will be used to conduct a formal scoping review of current literature to address the question: “What machine learning methods have been applied to influenza virus and coronavirus genome data for identification of the potential reservoirs?”. Eligibility Criteria: Eligible studies will be primary research studies, in English, from any geographic location, published between 2000-2021, conducted using machine learning techniques within the context of understanding or predicting influenza virus or coronavirus host-range or transmission. Sources of Evidence: The following databases will be searched: PubMed, MEDLINE, ProQuest, Engineering Village, and Web of Science from 2000-2021. Charting Methods: We will extract data on general and specific study characteristics, identifying the steps taken in data gathering, processing, and analysis.en_US
dc.description.sponsorshipThis work will be funded by OMAFRA and the First Canada Research Excellence Fund.en_US
dc.identifier.urihttps://hdl.handle.net/10214/26112
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectmachine learningen_US
dc.subjectcoronavirusen_US
dc.subjectgenome dataen_US
dc.subjectinfluenza virusen_US
dc.subjectprotocolen_US
dc.titleThe Use of Machine Learning and Predictive Modelling Methods in the Identification of Hosts for Viral Infections: Scoping Review Protocolen_US
dc.typeResearch Protocolen

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