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The purpose of this study is to propose an analytical framework for generating main path analysis (MPA) and demonstrate the process involved in identifying, analyzing the MPA on a citation network and empirically testing in the research field chromosome anomalies (CA).

The proposed methodological structure involves five phases of the process. Search path method is used to measure the weights of each citation link from a source vertex to a sink vertex. The key route local main path and global main path are generated to identify the knowledge diffusion trajectories and validated by cross-referencing with existing literature, co-citation analysis and centrality measures of social network analysis.

The empirical validation of this framework within CA research demonstrates its potential for tracing knowledge diffusion and technological development trajectories over three decades. This approach elucidates two major intellectual knowledge flows. The first key-route main path identified the primary diagnostic protocols. The second key-route main path revealed that cancer or carcinogenesis is identified as one of the mainstream of CA.

The limitations of the data and coverage period restrict the scope of this study. MPA was applied exclusively to the most influential sub network and disregarded other sub networks. MPA identified the seminal papers that provided a historical development in diagnostic protocol and their interconnectedness of disorders and diseases. This helps the researchers to develop targeted therapies and interventions, especially in cancer treatment.

Exploiting MPA on CA research provides valuable insights to stakeholders in developing evidence-based public health policies. This is crucial for preventing the birth of children with birth defects or genetic diseases, promoting public health and reducing the socioeconomic burden on a country through enhanced surveillance and prevention efforts.

The study suggests that in addition to traditional scientometrics measures, MPA can be used to trace the evolution of knowledge and technological advancements. It also highlights the role of social network analysis measures in extracting main paths.

The All India Institute of Medical Sciences (AIIMS) is a premier medical institution in India that has significantly contributed to cancer research. This study aims to highlight the cancer research productivity of AIIMS by assessing the impact and reach of the institution’s research output.

The study was based on 2,078 published papers on cancer of AIIMS indexed in the Web of Science (WoS) database from 1989 to 2021. A combination of tools such as Microsoft Excel, Biblioshiny, BibExcel and VOSviewer was used to evaluate and visualize the selected data.

The analysis revealed the interdisciplinary nature of research outputs, which have collaborative contributions from various fields such as oncology, pathology, radiology and surgery. The most productive research area within cancer was found to be breast cancer. In terms of international collaboration, the analysis revealed that AIIMS has a strong presence in the global cancer research community, with collaborations with researchers from more than 50 countries.

This study has some limitations. First, the study is limited to using only the WoS Core Collection database. Other databases, such as Scopus and PubMed, were excluded. Second, there is ambiguity in author names and nonuniformity in the institutions’ names, which can significantly affect the study’s outcomes.

Identifying research productivity in cancer at AIIMS aids resource allocation, collaboration and strategic planning, enhancing India’s overall cancer research impact and patient outcomes.

To the best of the authors’ knowledge, this study is to use scientometric indicators to evaluate AIIMS’s research productivity with particular reference to cancer for the first time. This detailed analysis provides a deeper understanding of AIIMS’s contribution to cancer research and its potential implications.