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从数据到医学背景:医疗保健中分类的力量。

From data to medical context: the power of categorization in healthcare.

作者信息

Msheik Batoul, Mcheick Hamid, Hariri Sara, Adda Mehdi, Dbouk Mohamed

机构信息

Computer Science Département, Université du Québec à Chicoutimi, Chicoutimi, QC, Canada.

Département de Mathématiques, Informatique et Génie, Université du Québec à Rimouski, Rimouski, QC, Canada.

出版信息

Front Med (Lausanne). 2025 Jun 11;12:1575195. doi: 10.3389/fmed.2025.1575195. eCollection 2025.

DOI:10.3389/fmed.2025.1575195
PMID:40568209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12187744/
Abstract

In the rapidly evolving healthcare domain, the ability to structure and interpret contextual medical data is crucial for delivering personalized and efficient patient care. While many existing studies attempt to define medical context through diverse categorizations, they often lack completeness or applicability in the real-world healthcare domain. This paper introduces a novel and comprehensive context categorization model composed of fifteen well-defined categories, bridging the gap between theoretical models and practical requirements in telemonitoring systems for chronic disease management. By incorporating important but often overlooked components such as social determinants, Service Level Agreements (SLAs), and environmental factors our model enhances clarity and strengthens decision-making in clinical settings. We validate the applicability of this framework through detailed case studies on asthma, COPD, and cardiovascular diseases, demonstrating its utility in enhancing telehealth solutions and aiding early intervention strategies.

摘要

在快速发展的医疗领域,构建和解读上下文医疗数据的能力对于提供个性化且高效的患者护理至关重要。尽管许多现有研究试图通过不同的分类来定义医疗上下文,但它们在实际医疗领域中往往缺乏完整性或适用性。本文介绍了一种由十五个明确界定的类别组成的新颖且全面的上下文分类模型,弥合了慢性病管理远程监测系统中理论模型与实际需求之间的差距。通过纳入社会决定因素、服务水平协议(SLA)和环境因素等重要但常被忽视的组件,我们的模型提高了清晰度,并加强了临床环境中的决策制定。我们通过对哮喘、慢性阻塞性肺疾病(COPD)和心血管疾病的详细案例研究来验证该框架的适用性,证明其在增强远程医疗解决方案和辅助早期干预策略方面的效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/c028b95101d9/fmed-12-1575195-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/188c2b5bc86a/fmed-12-1575195-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/bdc8b7327236/fmed-12-1575195-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/3ded6c459705/fmed-12-1575195-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/5e37dabfbc2b/fmed-12-1575195-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/c028b95101d9/fmed-12-1575195-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/188c2b5bc86a/fmed-12-1575195-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/bdc8b7327236/fmed-12-1575195-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/3ded6c459705/fmed-12-1575195-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/5e37dabfbc2b/fmed-12-1575195-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3532/12187744/c028b95101d9/fmed-12-1575195-g005.jpg

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Trial of Endovascular Therapy for Acute Ischemic Stroke with Large Infarct.大面积梗死急性缺血性卒中血管内治疗试验
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《心脏病与卒中统计数据-2023 更新:美国心脏协会报告》。
Circulation. 2023 Feb 21;147(8):e93-e621. doi: 10.1161/CIR.0000000000001123. Epub 2023 Jan 25.
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Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review.可穿戴式智能设备在心血管疾病检测中的应用:系统文献回顾。
Sensors (Basel). 2023 Jan 11;23(2):828. doi: 10.3390/s23020828.
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