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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES

Abstract

In this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential challenges of using, storing and transferring sensitive patient data are discussed.

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Details

Category:
Articles
Type:
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Published in:
TASK Quarterly no. 21, pages 309 - 319,
ISSN: 1428-6394
Language:
English
Publication year:
2017
Bibliographic description:
Kwaśniewska A., Giczewska A., Rumiński J.: BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES// TASK Quarterly. -Vol. 21., nr. 4 (2017), s.309-319
DOI:
Digital Object Identifier (open in new tab) 10.17466/tq2017/21.4/s
Bibliography: test
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