Multi-level medical periodic patterns from human movement behaviors

Zhang, Dongzhi, Lee, Kyungmi, and Lee, Ickjai (2019) Multi-level medical periodic patterns from human movement behaviors. Health Information Science and Systems, 7 (1). 9.

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Human movement behaviors could reveal many interesting medical patterns. Due to the advances in location-aware devices, a large volume of human movement behaviors has been captured in the form of spatio-temporal trajectories. These spatio-temporal trajectories are useful resources for medical data mining, and they could be used to classify which trajectory passes through medical centres and which one does not. Traditional approaches utilise time-series datasets while ignoring spatio-temporal semantics in order to detect periodic patterns in medical domains. They also fail to consider the inherent hierarchical nature of patterns. We investigate a medical data mining framework that generates multi-level medical periodic patterns. A Geolife dataset is used to test the feasibility and applicability of our framework. Experiments demonstrate that the proposed framework successfully distinguishes those who periodically visit medical centres from those who do not, and also to find multi-level medical periodic patterns revealing interesting hierarchical medical behaviours. One potential application includes an automated personalised medical service. For instance, medical institutions can send personalised relative medicine information to people who regularly visit certain medical centres. It will be useful for the discovery and diagnosis of diseases for patients.

Item ID: 58573
Item Type: Article (Research - C1)
ISSN: 2047-2501
Keywords: periodic pattern mining; multi-level hierarchical patterns; spatio-temporal trajectories; medical patterns
Copyright Information: © Springer Nature Switzerland AG 2019.
Date Deposited: 19 Jul 2019 02:47
FoR Codes: 42 HEALTH SCIENCES > 4203 Health services and systems > 420399 Health services and systems not elsewhere classified @ 20%
46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460308 Pattern recognition @ 40%
46 INFORMATION AND COMPUTING SCIENCES > 4601 Applied computing > 460102 Applications in health @ 40%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970116 Expanding Knowledge through Studies of Human Society @ 100%
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