Recent deep learning models for dementia as point-of-care testing: Potential for early detection

Karako, Kenji; Song, Peipei; Yu, Chen

doi:10.5582/irdr.2023.01015

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…This feature makes it particularly valuable in areas such as medical imaging, electronic medical records, genomics, and drug development [12]. In addition, deep learning has been the subject of intense research over the past decade, with applications ranging from natural language processing to the early detection of diseases such as dementia [13]. In the field of pathology, recent progress in deep learning is easing the computational examination of histological samples, enhancing the diagnosis and understanding of diverse diseases [14].…”

Section: Introductionmentioning

confidence: 99%

A bibliometric analysis of the advance of artificial intelligence in medicine

Andrade-Arenas,

Yactayo-Arias

2024

IJECE

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This bibliometric study analyzes the evolution of research in artificial intelligence (AI) applied to medicine from 2015 to September 2023. Using the Scopus database and keywords related to AI, machine learning, and deep learning in medicine, tools such as VOSviewer and Bibliometrix were used to explore publication trends, subject areas, co-authorship networks, and the most productive countries, among others. 2,064 articles were analyzed, and a significant increase in global academic production has been evident in the last five years. International collaboration was notable, with China and the United States leading in knowledge contribution. The keyword analysis highlights the breadth of topics and applications of AI in medicine, with particular emphasis on cancer detection, dengue diagnosis, and medical image analysis, among others. In conclusion, this study highlights the growing academic interest in the application of AI in medicine and the need for collaborative research. The findings underscore the relevance of these technologies in key areas of health care, contributing significantly to advances in medical diagnosis and prognosis.

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Section: Introductionmentioning

confidence: 99%