A Bibliometric Approach to Track Research Trends in Computer-Aided Early Detection of Cancer Using Biomedical Imaging Techniques

Abstract

The paper’s primary goal is to conduct a comprehensive bibliometric analysis of scholarly publications related to computer-aided early detection of cancer using biomedical imaging techniques. Among many diseases, cancer is the second major cause of death in the world. Nevertheless, with advancements in cancer screening, the survival rate for many types of cancer is enhancing. If cancer is noticed in its early stage, it sets out the best chances for healing. Screening involves a physical examination, laboratory tests, imaging tests, and biopsy. According to research, imaging tests are the most accurate cancer diagnosis methods. This work seeks to acquire results from scholarly articles extracted from the Scopus database for the last two decades by analyzing growth in publications and sources, author’s endowment, keyword analysis, article citation frequencies, etc. To exhibit the bibliometric study, open-source tools, namely BiblioShiny, VOSviewer, Word Cloud, are utilized. The analysis indicates, 78.52% of publications are of article and review type. Breast cancer, segmentation, melanoma, and deep learning are often used keywords in scholarly articles. Substantial work has been done in China, followed by Germany and the USA under the Computer Science area; also, it shows the elevation in several publications since 2019. Our study will furnish a broad range of perceptions for upcoming researchers by tracking the research study trends. This bibliometric analysis will be worthwhile for an apprentice to survey ongoing research under cancer detection using biomedical images.