Artificial Intelligence Recommendation System of Cancer Rehabilitation Scheme Based on IoT Technology
| Autor: | Jianhui Wu, Shuqing Gao, Zhenguo Han, Ai-Min Yang, Dian-Bo Hua, Yang Han, Yanlong Yu |
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| Rok vydání: | 2020 |
| Předmět: |
Scheme (programming language)
IoT General Computer Science Computer science artificial intelligent recommendation system medicine.medical_treatment 02 engineering and technology Recommender system Convolutional neural network Field (computer science) 0202 electrical engineering electronic engineering information engineering medicine General Materials Science Operations management computer.programming_language cancer recovery Rehabilitation business.industry 020208 electrical & electronic engineering General Engineering Cancer medicine.disease BAS Optimal nutrition Cancer rehabilitation 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering InformationSystems_MISCELLANEOUS Internet of Things business lcsh:TK1-9971 computer CNN |
| Zdroj: | IEEE Access, Vol 8, Pp 44924-44935 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.2978078 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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