Machine Learning Algorithm for Cancer Prediction: A Bibliometric Review

The incidence of cancer is rising dramatically on a global scale. Many people receive a late-stage diagnosis despite though cancer is preventable and well-treated in its early stages. Furthermore, cancer frequently returns following protracted treatment. Therefore, it is essential to anticipate cancer recurrence to proactively pursue specific treatments. The study review literature done on machine learning algorithm for cancer prediction using bibliometric review and Vosviewer. The studies that were taken into consideration for this research were obtained from the Web of Science database. A range of search terms, such as pertinent keywords (Machine learning, cancer detection, cancer prediction), were utilized to examine the title, keywords, and abstract of articles inside the database covering the years 2014 through 2023. 1914 documents were used for the study. Articles published in IEEE Access have a greater impact, but Scientific Reports had received more citations than articles in other journals—roughly 1018 of all the citations for the chosen documents come from articles published in this journal. Research on International evaluation of an AI system for screening of breast cancer had the highest citations 1059. India has the highest documents of 430 representing 22.419%. For citations, the USA has the highest of 122,072. Egyptian Knowledge Bank EKB has the highest documents of 61 representing 3.180%. National Natural Science Foundation of China (NSFC) has the highest documents of 131 representing 6.830%. Machine learning must be incorporated into clinical practice and trials due to the changing nature of cancer and how it is treated over time.