Vetnuus | October 2024 13 Materials and Methods Ethical approval Ethical Committee approval was not required because the study was based on a systematic review. Study period and location The electronic databases PubMed, Embase, Google Scholar, and Scopus were thoroughly screened up to March 22, 2023, for the use of AI in veterinary medicine. The data were extracted at the Department of Veterinary Medicine, Russian StateAgrarian University, Moscow. Search strategy, selection criteria, and study selection The search strategy was developed based on our previous studies and was modified based on the co-authors’views. Article screening was conducted according to the most up-to-date guidelines for systematic reports and meta-analysis as outlined in PRISMA [6] and Cochrane [7]. The electronic databases PubMed, Embase, Google Scholar, and Scopus were thoroughly screened through March 22, 2023, for the use of AI in veterinary medicine. The keywords were terms relevant to animal species, veterinary medicine, and AI. All screenings were performed based on the publication title or the abstract if the full text was unavailable. Identified citations were imported into the Endo file. The approach process and identification of the reviewed articles are illustrated in the flow diagram (Figure 1). A population, intervention, control, and outcomes (PICO) note on external validity was attached to each citation. The study design was carefully chosen to provide quality evidence, as randomized trials without significant limitations provide high-quality and stronger evidence. No automatic filtration was applied in this search, and other references used for the search are listed in the appropriate part of the study. All aspects of AI, including ML, convolutional neural network (CNN), and deep learning (DL) were accepted as part of the search results. A total of 79 relevant studies were retrieved from the search criteria and were included in this study. Extracted/included data For a study to be included in the search, it had to have been an original research publication in a peer-reviewed journal, conference, or book accessible to the reviewers. There were no limitations regarding either country or language of origin of the study. The publication has to describe the use of AI in veterinary medicine. There were no restrictions on study design, and randomized or nonrandomized controlled trials, interventional, observational, or case studies were included. Failure to comply with the required criteria resulted in the exclusion of the publication. In addition, any duplicated publications were excluded from the study. Which category to assign each study to, as noted in Table 1, was discussed and agreed on by all co-authors. The authors developed a table containing 19 criteria specifically for use in extracting data from papers on the use of AI per individual speciality in the veterinary profession. It was agreed that a minimum of 30 reports were necessary to define a specific category. Any criterion with fewer than 30 studies was classified as part of the diverse category. This threshold significantly decreased the number of different criteria and maximized the study’s ability to focus on critical AI orientation. Reviews and references obtained through the search were equally and randomly distributed to all co-authors, who individually screened them based on the study design criteria. There was a total of 19 articles that could have been attributed to more than one criterion. In this situation, all reviewers discussed their views until a consensus was reached. Two independent Exclusion criteria The publications with AI use but not related to veterinary medicine were excluded. Failure to comply with the required criteria resulted in the exclusion of the publication. In addition, any duplicated publications were excluded from the study. Article >>> 14 Figure-1: Flowchart of systematic review process.
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