Effectiveness of an artificial intelligence-based training and monitoring system in prevention of nosocomial infections: A pilot study of hospital-based data

  • Huang T
  • Ma Y
  • Li S
  • et al.
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Abstract

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.

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APA

Huang, T., Ma, Y., Li, S., Ran, J., Xu, Y., Asakawa, T., & Lu, H. (2023). Effectiveness of an artificial intelligence-based training and monitoring system in prevention of nosocomial infections: A pilot study of hospital-based data. Drug Discoveries & Therapeutics, 17(5), 351–356. https://doi.org/10.5582/ddt.2023.01068

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