Yan Zhang, Jian Cao, K. Shen, Xiao-song Chen, Siji Zhu
{"title":"A Multi-disciplinary Medical Treatment Decision Support System with intelligent treatment recommendation","authors":"Yan Zhang, Jian Cao, K. Shen, Xiao-song Chen, Siji Zhu","doi":"10.1109/COMPCOMM.2016.7924820","DOIUrl":null,"url":null,"abstract":"In order to decide a medical treatment plan for a patient, experts from different disciplines should come together to discuss. This process is often time-consuming and organized in an inefficient way. A multi-disciplinary medical treatment decision support system is proposed and developed in order to speed up this process. Specifically, this system can recommend treatment plan according to a patient's clinical information. It is based on k-NN algorithm to learn the appropriate treatment from a patient database. The system structure together with the recommendation approach is introduced. The experimental results are also presented, which show the availability and good performance of this recommendation approach.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPCOMM.2016.7924820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In order to decide a medical treatment plan for a patient, experts from different disciplines should come together to discuss. This process is often time-consuming and organized in an inefficient way. A multi-disciplinary medical treatment decision support system is proposed and developed in order to speed up this process. Specifically, this system can recommend treatment plan according to a patient's clinical information. It is based on k-NN algorithm to learn the appropriate treatment from a patient database. The system structure together with the recommendation approach is introduced. The experimental results are also presented, which show the availability and good performance of this recommendation approach.
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