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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Almeida, M. I., Rosa, Á. & Pestana, H. C. F. C. (2024). Emerging trends of artificial intelligence in healthcare: A bibliometric outlook. International Journal of Healthcare Technology and Management. 21 (1), 49-78
Exportar Referência (IEEE) 
M. I. Almeida et al.,  "Emerging trends of artificial intelligence in healthcare: A bibliometric outlook", in Int. Journal of Healthcare Technology and Management, vol. 21, no. 1, pp. 49-78, 2024
Exportar BibTeX 
@article{almeida2024_1744070501057,
	author = "Almeida, M. I. and Rosa, Á. and Pestana, H. C. F. C.",
	title = "Emerging trends of artificial intelligence in healthcare: A bibliometric outlook",
	journal = "International Journal of Healthcare Technology and Management",
	year = "2024",
	volume = "21",
	number = "1",
	doi = "10.1504/IJHTM.2024.136548",
	pages = "49-78",
	url = "https://www.inderscienceonline.com/journal/ijhtm"
}
Exportar RIS 
TY  - JOUR
TI  - Emerging trends of artificial intelligence in healthcare: A bibliometric outlook
T2  - International Journal of Healthcare Technology and Management
VL  - 21
IS  - 1
AU  - Almeida, M. I.
AU  - Rosa, Á.
AU  - Pestana, H. C. F. C.
PY  - 2024
SP  - 49-78
SN  - 1368-2156
DO  - 10.1504/IJHTM.2024.136548
UR  - https://www.inderscienceonline.com/journal/ijhtm
AB  - 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.
ER  -