School of Public Health and Management, Youjiang Medical University for Nationalities, Baise, 533000 Guangxi, China.
Innovation and Entrepreneurship College, Baise University, Baise, 533000 Guangxi, China.
Biomed Res Int. 2022 Aug 23;2022:9681769. doi: 10.1155/2022/9681769. eCollection 2022.
Surgery is one of the larger wounds in conventional surgery, and patients often experience different pain and postural discomfort after surgery. With the ever-changing standards of medical care and patient care requirements, providing high-quality care to postoperative patients is an important measure to reduce complications and promote rapid recovery. However, in the traditional postsurgical nursing methods, there are often the phenomenon that wrong patients are connected, patient data is messy, and medicines are counted incorrectly, which directly leads to a rapid decline in nursing efficiency. In the context of the rapid development of artificial intelligence and big data, intelligent medical data analysis technology has gradually been integrated into the medical field. This paper analyzes and studies the application effect of intelligent medical data analysis technology in postoperative nursing. It is aimed at changing the traditional postoperative nursing methods and improving nursing efficiency, and it provides important suggestions for the development of postoperative nursing in the new era. Combining big data and Internet of Things technology, this paper builds a smart medical Internet of Things framework and an intelligent postoperative care system and uses machine learning algorithms to preprocess relevant medical data. The final experimental results show that the intelligent medical data analysis technology has a good effect in improving the nursing efficiency after surgery, and the nursing efficiency has increased by 6.9%.
手术是传统外科中的较大创伤之一，患者术后常经历不同程度的疼痛和体位不适。随着医疗护理标准和患者护理要求的不断变化，为术后患者提供高质量的护理是减少并发症和促进快速康复的重要措施。然而，在传统的术后护理方法中，经常存在连接错误患者、患者数据混乱和药品计数错误等现象，这直接导致护理效率迅速下降。在人工智能和大数据飞速发展的背景下，智能医疗数据分析技术逐渐融入医疗领域。本文分析研究了智能医疗数据分析技术在术后护理中的应用效果。旨在改变传统的术后护理方法，提高护理效率，为新时代的术后护理发展提供重要建议。本文结合大数据和物联网技术，构建了智能医疗物联网框架和智能术后护理系统，并使用机器学习算法对相关医疗数据进行预处理。最终的实验结果表明，智能医疗数据分析技术在提高手术护理效率方面效果显著，护理效率提高了 6.9%。
