The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries

被引:163
作者
Guo, Jonathan [1 ]
Li, Bin [1 ,2 ]
机构
[1] Washington Inst Hlth Sci, Dept Social Med, Arlington, VA USA
[2] Georgetown Univ, Med Ctr, Dept Neurosci, 3800 Reservoir Rd NW, Washington, DC 20007 USA
关键词
artificial intelligence; developing countries; healthcare; rural areas; service network;
D O I
10.1089/heq.2018.0037
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Artificial intelligence (AI) is a rapidly developing computer technology that has begun to be widely used in the medical field to improve the professional level and efficiency of clinical work, in addition to avoiding medical errors. In developing countries, the inequality between urban and rural health services is a serious problem, of which the shortage of qualified healthcare providers is the major cause of the unavailability and low quality of healthcare in rural areas. Some studies have shown that the application of computer-assisted or AI medical techniques could improve healthcare outcomes in rural areas of developing countries. Therefore, the development of suitable medical AI technology for rural areas is worth discussing and probing. Methods: This article reviews and discusses the literature concerning the prospects of medical AI technology, the inequity of healthcare, and the application of computer-assisted or AI medical techniques in rural areas of developing countries. Results: Medical AI technology not only could improve physicians' efficiency and quality of medical services, but other health workers could also be trained to use this technique to compensate for the lack of physicians, thereby improving the availability of healthcare access and medical service quality. This article proposes a multilevel medical AI service network, including a frontline medical AI system (basic level), regional medical AI support centers (middle levels), and a national medical AI development center (top level). Conclusion: The promotion of medical AI technology in rural areas of developing countries might be one means of alleviating the inequality between urban and rural health services. The establishment of a multilevel medical AI service network system may be a solution.
引用
收藏
页码:174 / 181
页数:8
相关论文
共 53 条
[11]   Dermatologist-level classification of skin cancer with deep neural networks [J].
Esteva, Andre ;
Kuprel, Brett ;
Novoa, Roberto A. ;
Ko, Justin ;
Swetter, Susan M. ;
Blau, Helen M. ;
Thrun, Sebastian .
NATURE, 2017, 542 (7639) :115-+
[12]   Computer-assisted medical diagnosis for rural Sub-Saharan Africa [J].
Friedman, Edward A. .
IEEE TECHNOLOGY AND SOCIETY MAGAZINE, 2009, 28 (03) :18-27
[13]   Despite Substantial Progress In EHR Adoption, Health Information Exchange And Patient Engagement Remain Low In Office Settings [J].
Furukawa, Michael F. ;
King, Jennifer ;
Patel, Vaishali ;
Hsiao, Chun-Ju ;
Adler-Milstein, Julia ;
Jha, Ashish K. .
HEALTH AFFAIRS, 2014, 33 (09) :1672-1679
[14]  
Goher K M, 2017, Robotics Biomim, V4, P5, DOI 10.1186/s40638-017-0061-7
[15]   Artificial intelligence in medicine [J].
Hamet, Pavel ;
Tremblay, Johanne .
METABOLISM-CLINICAL AND EXPERIMENTAL, 2017, 69 :S36-S40
[16]   Patient safety and quality of care in developing countries in Southeast Asia: a systematic literature review [J].
Harrison, Reema ;
Cohen, Adrienne Wai Seung ;
Walton, Merrilyn .
INTERNATIONAL JOURNAL FOR QUALITY IN HEALTH CARE, 2015, 27 (04) :240-254
[17]  
Holl M, 2017, ARTIF INTELL
[18]  
HORROCKS JC, 1972, BMJ-BRIT MED J, V2, P5, DOI 10.1136/bmj.2.5804.5
[19]  
International Labour Office, 2015, GLOBAL EVIDENCE INEQ
[20]   Acute leukemia classification by ensemble particle swarm model selection [J].
Jair Escalante, Hugo ;
Montes-y-Gomez, Manuel ;
Gonzalez, Jesus A. ;
Gomez-Gil, Pilar ;
Altamirano, Leopoldo ;
Reyes, Carlos A. ;
Reta, Carolina ;
Rosales, Alejandro .
ARTIFICIAL INTELLIGENCE IN MEDICINE, 2012, 55 (03) :163-175