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UNSTRUCTURED Cervical cancer (CC) ranks fourth for both incidence and mortality among cancers in women globally, indicating that this cancer remains a heavy burden worldwide despite the development and application of prophylactic HPV vaccines and effective screening and early detection methods. Radical surgery and radiation therapy can achieve a good prognosis for early-stage cervical cancers. However, the efficacy of the current treatment modalities is unsatisfactory for advanced and recurrent cervical cancers, resulting in poor survival outcomes. Immunotherapy for advanced and recurrent cervical cancer patients is a promising approach. Numerous articles on these immunotherapy strategies have been published since 2010, but nothing is known about their research trends. In the era of information explosion, it is exceptionally time-consuming, energy-consuming, and inefficient to screen these numerous, uneven, and scattered publications. Bibliometric analysis that relies on an artificial intelligence-based algorithm can solve this problem well and help us quickly understand the hot spots and trends in a particular field. It can comprehensively offer a quantitative and statistical analysis of publications in specific areas， analyze the development of a discipline, and intuitively understand frontier trends by presenting numerous data in the form of knowledge maps. CreateSpace and VOSviewer are web-based Java applications for data analysis and visualization that are frequently used in bibliometric software. However, a little metrological literature study has been done on cervical cancer patients. In this study, we try to pinpoint research hot spots and trends through an integrative analysis of pertinent data from articles published globally between 2002 and 2022.