基于认知计算的患者驾驶评估医疗决策支持系统

Oleksiy Khriyenko, Chinh Nguyen Kim, Atte Ahapainen
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引用次数: 3

摘要

明智地利用庞大且不断增长的数据量,提高生产力,增加生活各个领域的竞争力;人类需要有效处理和分析数据的决策支持系统,从而显著加快决策过程。与人类生活的所有其他领域类似,医疗保健领域也缺乏基于人工智能(AI)的解决方案。有许多有监督和无监督的机器学习和数据挖掘技术可以帮助我们处理结构化数据。然而,在现实生活中,我们处理的非结构化数据往往隐藏在人类可读的纯文本、图像、音频和视频中,这些数据隐藏了有用的知识和有价值的信息。因此,IBM、Google、Microsoft、Intel、Facebook等IT巨头以及各类中小企业都在积极开发不同的认知计算服务和工具,从非结构化数据中获取价值。因此,本文提出了IBM Watson认知计算服务和工具的可行性研究,以解决自动健康记录处理问题,以支持医生对患者驾驶评估的决策。
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Cognitive Computing supported Medical Decision Support System for Patient’s Driving Assessment
To smartly utilize a huge and constantly growing volume of data, improve productivity and increase competitiveness in various fields of life; human requires decision making support systems that efficiently process and analyze the data, and, as a result, significantly speed up the process. Similarly to all other areas of human life, healthcare domain also is lacking Artificial Intelligence (AI) based solution. A number of supervised and unsupervised Machine Learning and Data Mining techniques exist to help us to deal with structured data. However, in a real life, we pretty much deal with unstructured data that hides useful knowledge and valuable information inside human-readable plain texts, images, audio and video. Therefore, such IT giants as IBM, Google, Microsoft, Intel, Facebook, etc., as well as variety of SMEs are actively elaborating different Cognitive Computing services and tools to get a value from unstructured data. Thus, the paper presents feasibility study of IBM Watson cognitive computing services and tools to address the issue of automated health records processing to support doctor’s decision for patient’s driving assessment.
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