A scientometric analysis of research trends, visualization, and emerging patterns in canine olfactory detection for cancer

Abstract

Background and Aim: Dogs can detect specific cancer odors with their exceptional sense of smell. This study aimed to conduct a scientometric analysis of canine olfactory detection in oncology, identifying trends, visualizations, and patterns. Materials and Methods: A retrospective observational study was conducted using a quantitative-scientometric approach. Scopus was comprehensively searched using terms related to canine olfactory detection in oncology. Documents indexed in Scival software (Elsevier) and published between 2013 and 2022 were included. Results: Claire M. Guest, Rob Harris, and Giuseppe Lippi authored significant academic work. Journals such as Journal of Breath Research and PLoS One rank highly in publications and citations due to significant citation ratios, according to CiteScore’s quartile-based impact analysis. According to Lotka’s and Bradford’s laws, a small group of authors and the Journal of Breath Research, respectively, dominate production in their fields. Conclusion: This analysis forms a solid base for future research on canine olfactory detection in oncology. The collaborative essence of this multidisciplinary field is emphasized by the key contributors and identified patterns, with journals in the Q1 and Q2 quartiles of CiteScore holding significant importance.

Keywords

• canine olfactory
• oncology
• scientometric