This study conducted a bibliometric analysis of radiomics ten years after the first work became available in March 2012. Throughout the analysis, the authors identified over 5,500 articles from almost 17,000 authors from over 900 different sources, highlighting developments within radiomics, its real-world applications, and tangible and intangible benefits.
- ML-based bibliometric analysis is fundamental to detect unknown pattern of data in Radiomics publications.
- A raising interest in the field, the most relevant collaborations, keywords co-occurrence network, and trending topics have been investigated.
- Some pitfalls still exist, including the scarce standardization and the relative lack of homogeneity across studies.
Authors: Stefania Volpe, Federico Mastroleo, Marco Krengli & Barbara Alicja Jereczek-Fossa