Evaluation Model for the Application of Artificial Intelligence Medical Assistant System to the Development of Medical Ecology in China

Chich-Jen Shieh, Guang-Sheng Wan, Wei Wang, Yuzhou Luo

Ekoloji, 2019, Issue 107, Pages: 311-316, Article No: e107036


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People are increasing the requirements for medical ecology in past years so that the establishment of an electronic medical care mechanism becomes urgent. Along with the development of network technology and the advance of information technology, electronic data could be done the statistical analysis. By extracting electronic medical records through the Internet, physicians could rapidly grasp complete medical record information for the diagnosis to further enhance medical quality and assist hospital managers in making proper decisions. Aiming at upper first-class hospitals in Shanghai, total 12 representative hospitals with artificial intelligence medical assistant systems are selected as the research objects for this study. Based on the annual statistical reports of the hospitals, “Delphi Method” and “Data Envelopment Analysis” are utilized for the data analyses. The research results are summarized as followings. 1. One DMU presents strong efficiency on the artificial intelligence medical assistant system performance, 4 DMUs show the efficiency in 0.9-1, and 5 DMUs appear the efficiency lower than 0.9. 2. Sensitivity analysis is utilized for analyzing and finding out the critical factors in the application of artificial intelligence medical assistant systems to medical ecology, and the inputs and outputs are gradually removed for DEA to understand the sensitivity to efficiency. According to the results, suggestions are proposed, expecting to provide medical ecology with the application of artificial intelligence medical assistant systems extracting data through diagnosis systems to perfect the medical record information of patients for physicians’ diagnoses and to further promote medical quality.


medical ecology, artificial intelligence, medical assistant system, performance evaluation


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