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The following is a summary of “Research Trends of Artificial Intelligence in Lung Cancer: A Combined Approach of Analysis With Latent Dirichlet Allocation and HJ-Biplot Statistical Methods,” published in the December 2024 issue of Pulmonology by De La Hoz-M et al.
Lung cancer (LC) continues to be a leading cause of cancer-related deaths globally, with artificial intelligence (AI) elevating and enhancing diagnostic and treatment methods.
Researchers conducted a retrospective study to provide updated insights into the role of AI in LC research by analyzing evolving topics, geographical distribution, and journal contributions.
They employed a unique method with latent Dirichlet allocation (LDA) topic modeling with the HJ-Biplot statistical technique to analyze AI research trends in LC, which allowed comprehensive exploration of evolving topics, geographical distribution, and contributions to journals.
The results showed a rising interest in AI applications in LC oncology, with an increase in publications after 2017, coinciding with advances in computing resources. Frontiers in Oncology led in publishing AI-related LC research. China and the United States were the main contributors, driven by an investment in R&D with corporate sector involvement. The LDA analysis specified key areas like pulmonary nodule detection, patient prognosis prediction, and clinical decision support systems, showing AI’s impact on LC outcomes. Deep learning (DL) and AI were evident, focusing on radiomics and feature selection for improved decision-making in LC care, AI research developed across topics like data analysis methods, tumor characterization, and predictive techniques, reflecting ongoing efforts to advance LC research. The HJ-Biplot visualization illustrated thematic clustering, illustrating temporal and geographical trends, indicating the contributions from high-impact journals and countries with advanced research capabilities.
Investigators concluded the insights into global collaboration patterns and research specialization in the LC field, highlighting AI’s growing influence in research and diagnosis.
Source: onlinelibrary.wiley.com/doi/full/10.1155/pm/5911646
