An ontological-based monitoring system for patients with bipolar I disorder

2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON) Pub Date : 2015-12-28 DOI:10.1109/SIBIRCON.2015.7361847

Chryssa H. Thermolia, E. Bei, E. Petrakis, V. Kritsotakis, V. Sakkalis

{"title":"An ontological-based monitoring system for patients with bipolar I disorder","authors":"Chryssa H. Thermolia, E. Bei, E. Petrakis, V. Kritsotakis, V. Sakkalis","doi":"10.1109/SIBIRCON.2015.7361847","DOIUrl":null,"url":null,"abstract":"Our aim is to provide a patient monitoring system that integrates a Clinical Decision Support System (CDSS) and an Electronic Health Record (EHR) that assist psychiatrists and primary care physicians to tackle existent health needs of mental illness related to the treatment and management of bipolar I disorder (BDI). Our monitoring system consists of an EHR system based on the Health Level Seven Reference Information Model (HL 7-RIM) and an ontological-based CDSS leveraging the Semantic Web capabilities. Based on the evidence-based clinical guidelines and patients' health records, the monitoring system is developed to encode and process this information and subsequently to assign recommendations of choices and alerts to clinicians for improved mental health care. Considering the clinical guidelines germane knowledge, as well as issues of patient's health record, the monitoring system can support a personalized decision-making for bipolar I disorder longitudinal course. We propose AI-CARE as an online monitoring tool that may offer useful guidance in clinical practice.","PeriodicalId":6503,"journal":{"name":"2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON)","volume":"6 1","pages":"43-49"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBIRCON.2015.7361847","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

Abstract

Our aim is to provide a patient monitoring system that integrates a Clinical Decision Support System (CDSS) and an Electronic Health Record (EHR) that assist psychiatrists and primary care physicians to tackle existent health needs of mental illness related to the treatment and management of bipolar I disorder (BDI). Our monitoring system consists of an EHR system based on the Health Level Seven Reference Information Model (HL 7-RIM) and an ontological-based CDSS leveraging the Semantic Web capabilities. Based on the evidence-based clinical guidelines and patients' health records, the monitoring system is developed to encode and process this information and subsequently to assign recommendations of choices and alerts to clinicians for improved mental health care. Considering the clinical guidelines germane knowledge, as well as issues of patient's health record, the monitoring system can support a personalized decision-making for bipolar I disorder longitudinal course. We propose AI-CARE as an online monitoring tool that may offer useful guidance in clinical practice.

查看原文本刊更多论文

基于本体的双相I型患者监测系统

我们的目标是提供一个整合临床决策支持系统(CDSS)和电子健康记录(EHR)的患者监测系统，帮助精神科医生和初级保健医生解决与双相I型障碍(BDI)治疗和管理相关的精神疾病的健康需求。我们的监测系统由基于健康级别7参考信息模型(hl7 - rim)的EHR系统和利用语义Web功能的基于本体的CDSS组成。根据循证临床指南和患者健康记录，开发了监测系统，对这些信息进行编码和处理，随后向临床医生分配选择建议和警报，以改善精神卫生保健。考虑到临床指南相关知识，以及患者健康记录的问题，监测系统可以支持I型双相情感障碍纵向病程的个性化决策。我们建议AI-CARE作为一种在线监测工具，可以为临床实践提供有用的指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON)

自引率

0.00%

发文量