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      How Technological Innovation Affect China's Pharmaceutical Smart Manufacturing Industrial Upgrading

      research-article
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      Journal of Healthcare Engineering
      Hindawi

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          Abstract

          In recent years, a new generation of information technology has provided sufficient technical support for the smart manufacturing industry. In order to promote the upgrading of China's pharmaceutical smart manufacturing industry, the direction of industrial upgrading and transformation will be discussed from the perspective of technological innovation. According to the input and output data of technological innovation in China's pharmaceutical manufacturing industry from 2007 to 2019, the DEA method is used to analyze the allocation of innovative resources in China's pharmaceutical manufacturing industry in recent years. The study found that the efficiency of technological innovation in China's pharmaceutical manufacturing industry fluctuated greatly from 2007 to 2019, with a low overall level and varying degrees of wasted resources. On this basis, an in-depth analysis of the system architecture of the pharmaceutical smart manufacturing industry under the Industry 4.0 environment was performed. Finally, four paths for the digital transformation of China's pharmaceutical manufacturing industry are proposed. Chinese pharmaceutical manufacturing companies need to use new technologies to carry out comprehensive intelligent upgrading and digital transformation to improve innovation efficiency.

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          Most cited references34

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            High-performance medicine: the convergence of human and artificial intelligence

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            The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient-doctor relationship or facilitate its erosion remains to be seen.
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                Author and article information

                Contributors
                Journal
                J Healthc Eng
                J Healthc Eng
                JHE
                Journal of Healthcare Engineering
                Hindawi
                2040-2295
                2040-2309
                2021
                26 November 2021
                : 2021
                : 3342153
                Affiliations
                School of Business Administration, Shenyang Pharmaceutical University, Shenyang 110016, China
                Author notes

                Academic Editor: Kalidoss Rajakani

                Author information
                https://orcid.org/0000-0001-8894-4003
                https://orcid.org/0000-0003-1804-4653
                Article
                10.1155/2021/3342153
                8642005
                3da977e7-89b7-4a2f-9727-3a1d11aa0688
                Copyright © 2021 Su Wang and Yuwen Chen.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 September 2021
                : 2 November 2021
                Categories
                Research Article

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