Machine Learning Technology and Application in the Health Sector: Bibliometric Analysis Mapping and Trends

Recently, machine learning is rapidly transforming the healthcare sector, offering innovative solutions to a wide range of medical challenges. This article presents a comprehensive bibliometric analysis of research on machine learning (ML) applications in healthcare, mapping the growth and trends from 2019 to 2024. Two keywords were used to search in the Scopus database, which were “machine learning” and “healthcare”. The search included title, abstract, and keywords, refining results to focus on the health sector’s application of ML. The results revealed that there is a sharp increase in research output, with the number of publications rising from 56 in 2019 to 2210 in 2023, and 2014 articles already published by September 2024. The 20 most published authors had between 69 and 34 documents. The countries dominating in research are the United States and India, each with over 1800 publications, followed by China, the United Kingdom, and Saudi Arabia. Other related keywords that emerged were “artificial intelligence”, “deep learning”, and “healthcare”, which suggested a strong focus on the application of ML in improving medical services, quality of life, and gender-specific health issues. The study highlights that ML technologies have great potential to improve clinical decision-making, enhance operational efficiency, provide more personalized treatment options, and improve the overall health services delivery.