Tianshui First People's Hospital, Tianshui 741000, China.
The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325000, China.
J Healthc Eng. 2021 Jun 4;2021:4874545. doi: 10.1155/2021/4874545. eCollection 2021.
Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify the corresponding chronic diseases, it can effectively reduce the labor cost, improve the accuracy of disease identification, and improve treatment efficiency. ADHD is a common behavioral disorder in school-age children, and it is also one of the most common chronic health problems in this period. The internationally recognized prevalence of ADHD is 3%-9%. ADHD often brings adverse effects on children's life and studying and at the same time increases difficulties for their families. Therefore, this paper designs an intelligent management platform for public hospitals based on a deep learning algorithm, evaluates the current situation and influencing factors of ADHD children through the child adaptive behavior scale and the family function assessment scale, and designs its intelligent platform by using a new technology of fNIRS. According to the nonlinearity and unsteadiness of the fNIRS signal, this paper proposes a motion noise removal method based on EMD algorithm methods: to automatically identify children with ADHD and improve the cognitive function of children with ADHD by intervention technology. The data are from the outpatients of the Department of Child Psychology of the First People's Hospital of Tianshui City in Gansu Province in 2018. The results showed that there were significant differences in the adaptive behavior scale (CABS) and fad scores between the two groups. In the seven dimensions of family function, there were significant differences between the two groups ( < 0.01). fNIRS management platform can effectively identify ADHD patients with high recognition accuracy. The intelligent management platform can significantly reduce the number of physical examination personnel, prolong the diagnosis and treatment time, reduce a lot of repetitive work, and improve the efficiency of diagnosis and treatment. At the same time, this technology also provides great help for better research and improvement of ADHD patients and provides a reference for the information intelligent construction of modern hospitals.
慢性病正逐渐成为人类健康的主要威胁。通过设计一个高效的医院管理平台，快速识别相应的慢性病，可以有效降低劳动力成本，提高疾病识别的准确性，提高治疗效率。ADHD 是学龄儿童常见的行为障碍，也是这一时期最常见的慢性健康问题之一。国际公认的 ADHD 患病率为 3%-9%。ADHD 常给儿童的生活和学习带来不良影响，同时也给家庭带来困难。因此，本文设计了一个基于深度学习算法的公立医院智能管理平台，通过儿童适应行为量表和家庭功能评估量表评估 ADHD 儿童的现状和影响因素，并利用 fNIRS 的新技术设计其智能平台。根据 fNIRS 信号的非线性和非平稳性，本文提出了一种基于 EMD 算法的运动噪声去除方法：通过干预技术自动识别 ADHD 儿童，并提高 ADHD 儿童的认知功能。数据来自 2018 年甘肃省天水市第一人民医院儿童心理科的门诊患者。结果表明，两组儿童在适应行为量表（CABS）和 fad 评分上存在显著差异。在家庭功能的七个维度上，两组之间存在显著差异（ < 0.01）。fNIRS 管理平台可以有效识别 ADHD 患者，识别准确率高。智能管理平台可以有效减少体检人员数量，延长诊断和治疗时间，减少大量重复性工作，提高诊断和治疗效率。同时，该技术也为更好地研究和改善 ADHD 患者提供了很大的帮助，为现代医院的信息化建设提供了参考。
