The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy
With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop t...
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| Veröffentlicht in: | Computational intelligence and neuroscience 2022-08, Vol.2022, p.1-12 |
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| creator | Li, Xiaohua Tan, Benren Zheng, Jinkun Xu, Xiaomei Xiao, Jian Liu, Yanlin |
| description | With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals. |
| doi_str_mv | 10.1155/2022/5371575 |
| format | Article |
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Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2022/5371575</identifier><identifier>PMID: 36045963</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Analysis ; Artificial intelligence ; Automation ; Big Data ; Data analysis ; Data mining ; Dispensing ; Dispensing machines ; Drug delivery ; Drug delivery systems ; Drug stores ; Drugs ; Drugstores ; Efficiency ; Emergency equipment ; Forecasts and trends ; Information systems ; Inventory ; Knowledge discovery ; Medical research ; Medicine ; Medicine, Experimental ; Patients ; Pharmaceutical industry ; Pharmacy ; Risk management ; Software ; Technical services ; Technology application ; Vehicles ; Web services</subject><ispartof>Computational intelligence and neuroscience, 2022-08, Vol.2022, p.1-12</ispartof><rights>Copyright © 2022 Xiaohua Li et al.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Xiaohua Li et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Xiaohua Li et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c453t-c01885641f39d01756d33eda436ccc5c19bc07726aed2a727dc0fd83a098ce6c3</citedby><cites>FETCH-LOGICAL-c453t-c01885641f39d01756d33eda436ccc5c19bc07726aed2a727dc0fd83a098ce6c3</cites><orcidid>0000-0002-6461-8745</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9423971/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9423971/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids></links><search><contributor>Sun, Le</contributor><contributor>Le Sun</contributor><creatorcontrib>Li, Xiaohua</creatorcontrib><creatorcontrib>Tan, Benren</creatorcontrib><creatorcontrib>Zheng, Jinkun</creatorcontrib><creatorcontrib>Xu, Xiaomei</creatorcontrib><creatorcontrib>Xiao, Jian</creatorcontrib><creatorcontrib>Liu, Yanlin</creatorcontrib><title>The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy</title><title>Computational intelligence and neuroscience</title><description>With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.</description><subject>Analysis</subject><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Big Data</subject><subject>Data analysis</subject><subject>Data mining</subject><subject>Dispensing</subject><subject>Dispensing machines</subject><subject>Drug delivery</subject><subject>Drug delivery systems</subject><subject>Drug stores</subject><subject>Drugs</subject><subject>Drugstores</subject><subject>Efficiency</subject><subject>Emergency equipment</subject><subject>Forecasts and trends</subject><subject>Information systems</subject><subject>Inventory</subject><subject>Knowledge discovery</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Medicine, 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neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Xiaohua</au><au>Tan, Benren</au><au>Zheng, Jinkun</au><au>Xu, Xiaomei</au><au>Xiao, Jian</au><au>Liu, Yanlin</au><au>Sun, Le</au><au>Le Sun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy</atitle><jtitle>Computational intelligence and neuroscience</jtitle><date>2022-08-22</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>1687-5265</issn><eissn>1687-5273</eissn><abstract>With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.</abstract><cop>New York</cop><pub>Hindawi</pub><pmid>36045963</pmid><doi>10.1155/2022/5371575</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-6461-8745</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Analysis Artificial intelligence Automation Big Data Data analysis Data mining Dispensing Dispensing machines Drug delivery Drug delivery systems Drug stores Drugs Drugstores Efficiency Emergency equipment Forecasts and trends Information systems Inventory Knowledge discovery Medical research Medicine Medicine, Experimental Patients Pharmaceutical industry Pharmacy Risk management Software Technical services Technology application Vehicles Web services |
| title | The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy |
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