Abstract
Based on the advantages of Internet of things, this paper focuses on the research of intelligent recommendation model for cancer patients' 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%. 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% of simulation results and 50% 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%. 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.
Highlights
Internet of things medicine is the application of IoT theory in medicine
The convolutional neural network structure designed in this paper considers that the sample data is 6 indexes
In this paper, the Convolutional neural network (CNN) algorithm and the Beetle Antennae Search (BAS) algorithm are coupled under the framework of the Internet of Things technology and embedded into the intelligent recommendation system
Summary
Internet of things medicine is the application of IoT theory in medicine. It contains three basic processes of perception, transmission, and intelligent processing, as well as ten functions of online monitoring, positioning and tracing, alarm linkage, plan management, hidden safety hazards, and statistical decision-making [1]. Under the framework of Internet of things medical technology, the establishment of an intelligent recommendation system for cancer rehabilitation integrating prediction and optimization model will be a blessing for cancer patients. By letting artificial intelligence algorithm learn CT images of cancer that far exceed the lifetime number of visits by human doctors, it trains a deep convolutional neural network model to detect the canceration of normal cells, so as to achieve the purpose of early detection and treatment. Prostate cancer is known to be the most common and second-deadliest cancer in American men, and classification of prostate cancer based on the Gleason histological image is important in patient risk assessment and treatment planning To solve this problem, the regional convolutional neural network model was used to detect epithelial cells and predict the risk of cancer.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
