Abstract
Currently, the Internet provides access to the large amount of public data describing various aspects of the healthcare system. Still, the available data has high diversity in its availability, quality, format, etc. The issues regarding collection, processing and integration of such diverse data can be overcome through the holistic semantic-based analysis of the data with data-driven predictive modeling supporting systematic checking and improving the quality of the data. This paper presents an ongoing work aimed to develop a flexible approach for holistic healthcare process analysis through integration of both private and public data of various types to support enhanced applications development: personalized health trackers, clinical decision support systems, solution for policy optimization, etc. The proposed approach is demonstrated on several experimental studies for collection and integration of data publicly available on the Internet within the context of data-driven predictive modeling in the healthcare.
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Acknowledgements
This research is financially supported by The Russian Scientific Foundation, Agreement #17-15-01177.
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Metsker, O.G. et al. (2019). Holistic Monitoring and Analysis of Healthcare Processes Through Public Internet Data Collection. In: Bodrunova, S., et al. Internet Science. INSCI 2018. Lecture Notes in Computer Science(), vol 11551. Springer, Cham. https://doi.org/10.1007/978-3-030-17705-8_4
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DOI: https://doi.org/10.1007/978-3-030-17705-8_4
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