{"title":"解读数据:将复杂性转化为改善慢性疼痛管理","authors":"L. Hepburn, E. Jaatun","doi":"10.1109/HealthCom.2018.8531162","DOIUrl":null,"url":null,"abstract":"Chronic pain is recognised as a complex and challenging condition. In Scotland alone, over 800,000 people are affected by chronic pain to varying degrees [1]. The experience of living with, and delivering treatment and care for chronic pain therefore requires a management strategy that responds effectively within a complex context. Management strategies should be interdisciplinary and take into account the many stakeholders involved, including the person experiencing chronic pain. This paper outlines the role for visualisation and machine learning to support people to make sense of data and enable the translation of the complexity around chronic pain towards better management, and in particular self-management.","PeriodicalId":232709,"journal":{"name":"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Making Sense of Data : Translating complexity for improved chronic pain management\",\"authors\":\"L. Hepburn, E. Jaatun\",\"doi\":\"10.1109/HealthCom.2018.8531162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Chronic pain is recognised as a complex and challenging condition. In Scotland alone, over 800,000 people are affected by chronic pain to varying degrees [1]. The experience of living with, and delivering treatment and care for chronic pain therefore requires a management strategy that responds effectively within a complex context. Management strategies should be interdisciplinary and take into account the many stakeholders involved, including the person experiencing chronic pain. This paper outlines the role for visualisation and machine learning to support people to make sense of data and enable the translation of the complexity around chronic pain towards better management, and in particular self-management.\",\"PeriodicalId\":232709,\"journal\":{\"name\":\"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2018.8531162\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2018.8531162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Making Sense of Data : Translating complexity for improved chronic pain management
Chronic pain is recognised as a complex and challenging condition. In Scotland alone, over 800,000 people are affected by chronic pain to varying degrees [1]. The experience of living with, and delivering treatment and care for chronic pain therefore requires a management strategy that responds effectively within a complex context. Management strategies should be interdisciplinary and take into account the many stakeholders involved, including the person experiencing chronic pain. This paper outlines the role for visualisation and machine learning to support people to make sense of data and enable the translation of the complexity around chronic pain towards better management, and in particular self-management.