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Artificial Intelligence Recommendation System of Cancer Rehabilitation Scheme Based on IoT Technology

机译:基于物联网技术的癌症康复方案人工智能推荐制度

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Based on the advantages of Internet of things, this paper focuses on the research of intelligent recommendation model for cancer patients & x2019; rehabilitation, and designs a user-friendly intelligent recommendation system of cancer rehabilitation scheme. In view of the uncertainty of the cause and time of recurrence of cancer patients, the convolutional neural network algorithm was used to predict both of them. The prediction results of the model showed that the prediction accuracy was high, reaching 92 & x0025;. To solve the problem of the optimal nutrition program for the rehabilitation of cancer patients, we took the recurrence time as the objective function, and established the recommendation model of the optimal nutrition support program for the rehabilitation by using BAS algorithm. Finally, under the framework of Internet of things technology, the intelligent recommendation model of cancer rehabilitation prediction model and nutrition support program was integrated to realize the recommendation system of intelligent recommendation of rehabilitation nutrition support program for cancer rehabilitation patients according to their different characteristics. After the system simulation experiment, it was found that under the condition that the predicted recurrence location was almost unchanged (49 & x0025; of simulation results and 50 & x0025; of actual results), the nutritional support scheme recommended by the intelligent recommendation system could extend the postoperative recurrence time of patients by more than 95 & x0025;. This recommendation system can help doctors select personalized nutrition and rehabilitation programs suitable for patients in the later stage of rehabilitation treatment according to different cancer patients, and has certain guiding significance for the field of cancer rehabilitation.
机译:本文基于互联网的优势,侧重于癌症患者智能推荐模型与X2019的研究;康复,设计了一种用户友好的癌症康复计划智能推荐系统。鉴于癌症患者复发的原因和时间的不确定性,卷积神经网络算法用于预测它们两个。该模型的预测结果表明预测精度高,达到92&x0025;为了解决癌症患者康复的最佳营养计划的问题,我们将复发时间作为客观函数,并通过使用BAS算法建立了康复的最佳营养支持计划的推荐模型。最后,根据事物互联网技术框架,癌症康复预测模型和营养支持方案的智能推荐模型综合地实现了癌症康复患者康复营养支持方案智能建议建议制度,根据其不同的特征。在系统仿真实验之后,发现在预测的复发位置几乎不变的情况下(49&x0025;实际结果和50&x0025;实际结果),智能推荐系统推荐的营养支持方案可以延长患者的术后复发时间超过95〜x0025;本建议权系统可以帮助医生选择适用于康复治疗后期患者的个性化营养和康复计划,根据不同的癌症患者,对癌症康复领域具有一定的指导意义。

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