Cognitive Computing supported Medical Decision Support System for Patient’s Driving Assessment

O. Khriyenko, C. Nguyen Kim, A. Ahapainen

Abstract


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.

Keywords


cognitive computing; decision support system; medical record processing; natural language processing; semantic similarity; IBM Watson; medical ontology; driving assessment. I

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