Your browser doesn't support javascript.
loading
Effectiveness of an artificial intelligence-based training and monitoring system in prevention of nosocomial infections: A pilot study of hospital-based data.
Huang, Ting; Ma, Yue; Li, Shaxi; Ran, Jianchao; Xu, Yifan; Asakawa, Tetsuya; Lu, Hongzhou.
Affiliation
  • Huang T; Department of Healthcare-associated Infection Management, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Ma Y; Department of Healthcare-associated Infection Management, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Li S; Department of Healthcare-associated Infection Management, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Ran J; Department of Healthcare-associated Infection Management, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Xu Y; Department of Healthcare-associated Infection Management, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Asakawa T; Institute of Neurology, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
  • Lu H; Institute of Neurology, National Clinical Research Center for Infectious Diseases, the Third People's Hospital of Shenzhen, Shenzhen, Guangdong, China.
Drug Discov Ther ; 17(5): 351-356, 2023 Nov 18.
Article in En | MEDLINE | ID: mdl-37673650
This work describes a novel artificial intelligence-based training and monitoring system (AITMS) that was used to control and prevent nosocomial infections (NIs) by improving the skills of donning/removing personal protective equipment (PPE). The AITMS has two working modes, namely an AI-based protective equipment surveillance mode and an AI-based training mode, that were used for routine surveillance and training, respectively. Data revealed that the accuracy rate of donning/removing PPE improved as a result of the AITMS. Interestingly, the frequency of NIs decreased with the use of the AITMS. This study suggested the key role of using PPE in controlling and preventing NIs. Data preliminarily proved that appropriate donning/removing PPE may help to reduce the risk of NIs. In addition, the newest computerized technologies, such as AI, have proven to be useful in controlling and preventing NIs. These findings should helpful to formulate a better strategy against NIs in the future.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Cross Infection Limits: Humans Language: En Journal: Drug Discov Ther Year: 2023 Document type: Article Affiliation country: China Country of publication: Japan

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Cross Infection Limits: Humans Language: En Journal: Drug Discov Ther Year: 2023 Document type: Article Affiliation country: China Country of publication: Japan