Emerging trends of artificial intelligence in healthcare: a bibliometric outlook

被引:1
|
作者
Almeida, Maria Ines [1 ]
Rosa, Alvaro [2 ]
Pestana, Helena Castelao Figueira Carlos [3 ]
机构
[1] Inst Univ Lisboa ISCTE IUL, Lisbon, Portugal
[2] Inst Univ Lisboa ISCTE IUL, Business Res Unit BRU IUL, Lisbon, Portugal
[3] Inst Univ Lisboa ISCTE IUL, ISCTE Execut Educ, Lisbon, Portugal
关键词
artificial intelligence; machine learning; deep learning; health; bibliometric analysis; LEARNING ALGORITHM; SCIENCE; WEB; CLASSIFICATION; VALIDATION; EVOLUTION; FUTURE; SCOPUS;
D O I
10.1504/IJHTM.2024.136548
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Emerging technologies are reshaping the landscape of healthcare, with artificial intelligence (AI) spearheading this transformative wave. The exploration of AI within the realm of healthcare is rapidly growing across multiple domains of medicine, with the aim of enhancing the healthcare sector by enabling tailored approaches to diagnosis, prognosis, and patient interventions. This study aims to understand the emerging applications of AI to aid the emergence and implementation of precision medicine. A descriptive bibliometric analysis and a conceptual structure analysis were carried out for this purpose. Our findings suggest that machine and deep learning models are primarily employed for disease diagnosis and prognosis, with a stronger emphasis on clinical specialties like cardiovascular and pulmonary conditions, as well as oncology and radiology. The current and upcoming focus of research revolves around the prominent subject of big data analysis, encompassing the following fundamental data science techniques: segmentation, classification, and processing of medical imaging.
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页数:31
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