The lookAfterRisk Project: Dynamic Cardiovascular Risk Assessment based on Remote Monitoring Solutions

Simão Paredes, J. Henriques, T. Rocha, P. Carvalho, J. Morais, Luis Santos, R. Carvalho
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引用次数: 2

Abstract

The LookAfterRisk project addresses the management of myocardial infarction (MI) patients. The main goal is the development of models for cardiovascular (CV) risk assessment of acute events integrating data from home-mobile technologies, in order to stratify patients according to their care needs. The models are applied at hospital admission, in patients with a first episode of acute MI and are continuously updated when the patient returns home.The scientific goal is the use of computational intelligence methodologies for the development of personalized, interpretable and dynamic models in the risk assessment of acute events, i.e., death/re-hospitalization. Three major scientific challenges are addressed: i) extraction of knowledge from recent datasets using data mining approaches; ii) integration of this knowledge with clinical evidence in a meaningful and interpretable way; iii) update of risk level based on data periodically collected at home during the follow up period.The result is an integrated tele-monitoring platform, merging the advantages of the continuous monitoring provided by low cost mobile technologies with prediction models.The validation is performed in the hospital admission using the largest MI Portuguese dataset (N=16000), provided by the Portuguese Society of Cardiology (PSC). The second phase is based on a home telemonitoring observational study (9 months), involving 50 patients (admitted with a first episode of acute MI). The data collected at patient’s home will be: blood pressure, heart rate, cholesterol and glycaemia. The project lasts 36 months; the team is composed by University of Coimbra, Leiria Hospital Centre and has the commitment of SPC.
lookAfterRisk项目:基于远程监测解决方案的动态心血管风险评估
LookAfterRisk项目致力于心肌梗死(MI)患者的管理。主要目标是开发急性事件心血管(CV)风险评估模型,整合来自家庭移动技术的数据,以便根据患者的护理需求对患者进行分层。该模型应用于住院时,首次发作急性心肌梗死的患者,并在患者返回家中时不断更新。科学目标是利用计算智能方法在急性事件(即死亡/再次住院)的风险评估中开发个性化、可解释和动态模型。解决了三个主要的科学挑战:i)使用数据挖掘方法从最近的数据集中提取知识;Ii)以有意义和可解释的方式将这些知识与临床证据相结合;Iii)根据随访期间在家中定期收集的数据更新风险水平。结果是一个集成的远程监测平台,将低成本移动技术提供的连续监测优势与预测模型相结合。验证是在入院时使用葡萄牙心脏病学会(PSC)提供的最大的MI葡萄牙数据集(N=16000)进行的。第二阶段是基于家庭远程监测观察性研究(9个月),涉及50例患者(首次急性心肌梗死发作)。在患者家中收集的数据包括:血压、心率、胆固醇和血糖。项目为期36个月;该小组由科英布拉大学、莱里亚医院中心组成,并有SPC的承诺。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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