Predicting cumulative effect of lifestyle risk factors for complex disease

IF 2.8 Q3 ENGINEERING, BIOMEDICAL
Emmanuel Effiok, Enjie Liu, Jon Hitchcock
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引用次数: 0

Abstract

In medical domain, risk factors are often used to model disease predictions. In order to make the most use of the predictive models, linking the model with real patient data generates personalized disease progression and predictions. However, the risk factors are fragmented all over medical literature, certain risks can be accumulated for a disease and the aggregated probability may increase or decrease the occurrence of a disease. In this paper, a risk predictive framework which forms a base for a complete risk prediction model that can be used for various health applications is proposed.

Abstract Image

预测复杂疾病的生活方式风险因素的累积效应
在医学领域,风险因素常用于疾病预测模型。为了最大限度地利用预测模型,将模型与真实患者数据联系起来,生成个性化的疾病进展和预测。然而,在所有的医学文献中,危险因素都是碎片化的,一种疾病可以积累一定的风险,其聚合概率可能会增加或减少疾病的发生。本文提出了一个风险预测框架,为建立一个完整的可用于各种卫生应用的风险预测模型奠定了基础。
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来源期刊
Healthcare Technology Letters
Healthcare Technology Letters Health Professions-Health Information Management
CiteScore
6.10
自引率
4.80%
发文量
12
审稿时长
22 weeks
期刊介绍: Healthcare Technology Letters aims to bring together an audience of biomedical and electrical engineers, physical and computer scientists, and mathematicians to enable the exchange of the latest ideas and advances through rapid online publication of original healthcare technology research. Major themes of the journal include (but are not limited to): Major technological/methodological areas: Biomedical signal processing Biomedical imaging and image processing Bioinstrumentation (sensors, wearable technologies, etc) Biomedical informatics Major application areas: Cardiovascular and respiratory systems engineering Neural engineering, neuromuscular systems Rehabilitation engineering Bio-robotics, surgical planning and biomechanics Therapeutic and diagnostic systems, devices and technologies Clinical engineering Healthcare information systems, telemedicine, mHealth.
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