微型电脑应用

基于电子病历大数据设计一种全新的智慧医疗分诊导医系统。综合利用超限学习机、多项式、对数、二值化等神经网络节点算法，构建一个拥有足够复杂度的神经网络系统，它可以完成以下人工智能判断，例如患者的IDC-11基准下的20个疾病代码的概率，以及为进一步确诊，建议患者的补充检查项目。在仿真环境下比较该系统分诊效率，发现该系统对比门诊医生分诊方案，患者平均检查次数降低45.53%,检查排队时间下降83.23%,总排队时间下降78.05%,确诊率提升198.10%,误诊率下降81.16%。医院门诊接诊能力获得了大幅度提升。如能够通过医疗伦理论证，该系统将对医院分诊能力和诊疗质量带来较大提升。

A new intelligent medical triage guidance system is designed based on big data of electronic medical record. A neural network system with enough complexity is constructed by comprehensively using neural network node algorithms such as transfinite learning machine, polynomial, logarithm and binarization, so that it can complete the following artificial intelligence judgment, including the probability of 20 disease codes under the IDC-11 benchmark of patients, and recommend supplementary examination items for further diagnosis. Comparing the triage efficiency of the system in the simulation environment, it is found that the average number of inspections of patients decreases by 45.53%, the queuing time decreases by 83.23%, the total queuing time decreases by 78.05%, the diagnosis rate increases by 198.10%, and the misdiagnosis rate decreases by 81.16%. The outpatient service capacity of the hospital is also greatly improved. If it can pass the medical ethics demonstration, the system will greatly improve the ability of triage and the quality of diagnosis and treatment.