Artificial Intelligence vs. Natural Stupidity: Evaluating AI Readiness for the Vietnamese Medical Information System
| Autor: | Hai Ha Giang, Manh-Toan Ho, Roger C.M. Ho, Quan-Hoang Vuong, Cyrus S.H. Ho, Manh Tung Ho, Bach Xuan Tran, Viet-Phuong La, Hong-Kong T. Nguyen, Carl A. Latkin, Thu-Trang Vuong, Kien Cuong P. Nghiem, Thu Vu Giang |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
AI readiness
Vietnamese media_common.quotation_subject Developing country lcsh:Medicine Context (language use) Review AI in medicine Field (computer science) AI applications 03 medical and health sciences 0302 clinical medicine Health care Medicine 030212 general & internal medicine 030304 developmental biology media_common 0303 health sciences Stupidity business.industry lcsh:R General Medicine artificial intelligence language.human_language Influencer marketing AI in healthcare Vietnam language Organizational structure Artificial intelligence business |
| Zdroj: | Journal of Clinical Medicine Journal of Clinical Medicine, Vol 8, Iss 2, p 168 (2019) |
| ISSN: | 2077-0383 |
| Popis: | This review paper presents a framework to evaluate the artificial intelligence (AI) readiness for the healthcare sector in developing countries: a combination of adequate technical or technological expertise, financial sustainability, and socio-political commitment embedded in a healthy psycho-cultural context could bring about the smooth transitioning toward an AI-powered healthcare sector. Taking the Vietnamese healthcare sector as a case study, this paper attempts to clarify the negative and positive influencers. With only about 1500 publications about AI from 1998 to 2017 according to the latest Elsevier AI report, Vietnamese physicians are still capable of applying the state-of-the-art AI techniques in their research. However, a deeper look at the funding sources suggests a lack of socio-political commitment, hence the financial sustainability, to advance the field. The AI readiness in Vietnam’s healthcare also suffers from the unprepared information infrastructure—using text mining for the official annual reports from 2012 to 2016 of the Ministry of Health, the paper found that the frequency of the word “database„ actually decreases from 2012 to 2016, and the word has a high probability to accompany words such as “lacking„, “standardizing„, “inefficient„, and “inaccurate.„ Finally, manifestations of psycho-cultural elements such as the public’s mistaken views on AI or the non-transparent, inflexible and redundant of Vietnamese organizational structures can impede the transition to an AI-powered healthcare sector. |
| Databáze: | OpenAIRE |
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