Medical Artificial Intelligence Research Landscape in Thailand: A Bibliometric Analysis

被引:1
|
作者
Kongthon, Alisa [1 ]
机构
[1] King Mongkuts Univ Technol Thonburi, Grad Sch Management & Innovat, Bangkok, Thailand
关键词
bibliometric analysis; text mining; medical artificial intelligence; research landscape; artificial intelligence in healthcare; COVID-19; SEGMENTATION; NETWORKS; PATTERNS; FEATURES; FUTURE; MODEL;
D O I
10.1109/iSAI-NLP60301.2023.10354993
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Over the past few years, artificial intelligence (AI) has evolved into a game-changing technology across various sectors. The endorsement of Thailand's national AI strategy and action plan (2022 - 2027) signifies a crucial step towards harnessing AI's benefits. With a focus on ten target sectors, the strategy aims to foster an ecosystem for AI development, enhancing the economy and the well-being of Thai citizens. Among these sectors, healthcare and medical stands prominently as an immediate priority. This paper applies bibliometric analysis on medical AI research publications to present an overview of Thailand's current medical AI research landscape. The analysis aims to identify the current medical AI experts and application areas of medical AI. With these insights, researchers, medical practitioners, and policy makers can better understand the development of medical AI research and possible practice implications.
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页数:6
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