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Erschienen in:
Internet of Things Driven Connected Healthcare Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Big Data Knowledge System in Healthcare

verfasst von : Gunasekaran Manogaran, Chandu Thota, Daphne Lopez, V. Vijayakumar, Kaja M. Abbas, Revathi Sundarsekar

Erschienen in: Internet of Things and Big Data Technologies for Next Generation Healthcare

Verlag: Springer International Publishing

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Abstract

The health care systems are rapidly adopting large amounts of data, driven by record keeping, compliance and regulatory requirements, and patient care. The advances in healthcare system will rapidly enlarge the size of the health records that are accessible electronically. Concurrently, fast progress has been made in clinical analytics. For example, new techniques for analyzing large size of data and gleaning new business insights from that analysis is part of what is known as big data. Big data also hold the promise of supporting a wide range of medical and healthcare functions, including among others disease surveillance, clinical decision support and population health management. Hence, effective big data based knowledge management system is needed for monitoring of patients and identify the clinical decisions to the doctor. The chapter proposes a big data based knowledge management system to develop the clinical decisions. The proposed knowledge system is developed based on variety of databases such as Electronic Health Record (EHR), Medical Imaging Data, Unstructured Clinical Notes and Genetic Data. The proposed methodology asynchronously communicates with different data sources and produces many alternative decisions to the doctor.

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Vorheriges Kapitel Internet of Things Meets Mobile Health Systems in Smart Spaces: An Overview
Nächstes Kapitel Big-Data Analytics, Machine Learning Algorithms and Scalable/Parallel/Distributed Algorithms
Literatur
1.
Manogaran, G., Thota, C., Kumar, M.: MetaCloudDataStorage architecture for Big Data security in cloud computing. Procedia Comput. Sci. 87, 128–133 (2016)CrossRef
2.
Victor, N., Lopez, D., Abawajy, J.: Privacy models for big data: a survey. Int. J. Big Data Intell. 3, 61 (2016)CrossRef
3.
Lopez, D., Sekaran, G.: Climate change and disease dynamics—a Big Data perspective. Int. J. Infect. Dis. 45, 23–24 (2016)CrossRef
4.
Lopez, D., Gunasekaran, M., Murugan, B.S., Kaur, H., Abbas, K.M.: Spatial Big Data analytics of influenza epidemic in Vellore, India. In: IEEE International Conference on Big Data, pp. 19–24, Oct 2014
5.
Bates, D., Saria, S., Ohno-Machado, L., Shah, A., Escobar, G.: Big Data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff. 33, 1123–1131 (2014)CrossRef
6.
Jee Kim, G.: Potentiality of Big Data in the medical sector: focus on how to reshape the healthcare system. Healthc. Inform. Res. 19, 79 (2013)
7.
Chawla, N., Davis, D.: Bringing Big Data to personalized healthcare: a patient-centered framework. J Gen. Intern. Med. 28, 660–665 (2013)
8.
Viceconti, M., Hunter, P., Hose, R.: Big Data, big knowledge: Big Data for personalized healthcare. IEEE J. Biomed. Health Inform. 19, 1209–1215 (2015)CrossRef
9.
Lopez, D., Gunasekaran, M.: Assessment of vaccination strategies using fuzzy multicriteria decision making. In: Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO-2015), pp. 195–208. Springer International (2015)
10.
Kothari, A., Hovanec, N., Hastie, R., Sibbald, S.: Lessons from the business sector for successful knowledge management in health care: a systematic review. BMC Health Serv. Res. 11, 173 (2011)CrossRef
11.
Chen, E.T.: An observation of healthcare knowledge management. Commun. IIMA 13, 95–106 (2013)
12.
Denny, J.: Chapter 13: mining electronic health records in the genomics era. PLoS Comput. Biol. 8, e1002823 (2012)
13.
Jensen, P., Jensen, L., Brunak, S.: Mining electronic health records: towards better research applications and clinical care. Nat. Rev. Genet. 13, 395–405 (2012)CrossRef
14.
Poon, E., Keohane, C., Yoon, C., et al.: Effect of bar-code technology on the safety of medication administration. Obstet. Gynecol. Surv. 65, 629–630 (2010)CrossRef
15.
Belle, A., Thiagarajan, R., Soroushmehr, S.M., Navidi, F., Beard, D.A., Najarian, K.: Big data analytics in healthcare. BioMed. Res. Int. 10, 1–16 (2015)CrossRef
16.
Virmani, J., Dey, N., Kumar, V.: PCA-PNN and PCA-SVM based CAD systems for breast density classification. In: Applications of Intelligent Optimization in Biology and Medicine, pp. 159–180. Springer International Publishing (2016)
17.
Bhattacherjee, A., Roy, S., Paul, S., Roy, P., Kausar, N., Dey, N.: Classification approach for breast cancer detection using back propagation neural network: a study. In: Biomedical Image Analysis and Mining Techniques for Improved Health Outcomes, p. 210 (2015)
18.
Suri, J., Dey, N., Bose, S., Das, A., Chaudhuri, S.S., Saba, L., Shafique, S., Nicolaides, A.: 2084743 Diagnostic preservation of atherosclerotic ultrasound video for stroke telemedicine in watermarking framework. Ultrasound Med. Biol. 41(4), S133 (2015)CrossRef
19.
Dey, N., Mukhopadhyay, S., Das, A., Chaudhuri, S.S.: Analysis of P-QRS-T components modified by blind watermarking technique within the electrocardiogram signal for authentication in wireless telecardiology using DWT. Int. J. Image, Graph. Sign. Process. 4(7), 33 (2012)CrossRef
20.
Acharjee, S., Ray, R., Chakraborty, S., Nath, S., Dey, N.: Watermarking in motion vector for security enhancement of medical videos. In: IEEE International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), pp. 532–537, July 2014
21.
Bose, S., Acharjee, S., Chowdhury, S.R., Chakraborty, S., Dey, N.: Effect of watermarking in vector quantization based image compression. In: IEEE International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), pp. 503–508, July 2014
22.
Pal, A.K., Dey, N., Samanta, S., Das, A., Chaudhuri, S.S.: A hybrid reversible watermarking technique for color biomedical images. In: IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp. 1–6, Dec 2013
23.
Nandi, S., Roy, S., Dansana, J., Karaa, W.B.A., Ray, R., Chowdhury, S.R., Chakraborty, S., Dey, N.: Cellular automata based encrypted ECG-hash Code generation: an application in inter human biometric authentication system. Int. J. Comput. Netw. Inf. Secur. 6(11), 1 (2014)
24.
Biswas, S., Roy, A.B., Ghosh, K. and Dey, N.: A biometric authentication based secured ATM Banking System. Int. J. Adv. Res. Comput. Sci. Softw. Eng. ISSN, 2277
25.
Murray, C.J., Barber, R.M., Foreman, K.J., Ozgoren, A.A., Abd-Allah, F., Abera, S.F., Aboyans, V., Abraham, J.P., Abubakar, I., Abu-Raddad, L.J., Abu-Rmeileh, N.M.: Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition. The Lancet 386(10009), 2145–2191 (2015)CrossRef
26.
27.
28.
29.
Stevens, G., Alkema, L., Black, R., Boerma, J., Collins, G., Ezzati, M., Grove, J., Hogan, D., Hogan, M., Horton, R., Lawn, J., Marušić, A., Mathers, C., Murray, C., Rudan, I., Salomon, J., Simpson, P., Vos, T., Welch, V.: Guidelines for accurate and transparent health estimates reporting: the GATHER statement. PLoS Med. 13(6), e1002056 (2016)CrossRef
30.
Stevens, G., Alkema, L., Black, R., Boerma, J., Collins, G., Ezzati, M., Grove, J., Hogan, D., Hogan, M., Horton, R., Lawn, J., Marušić, A., Mathers, C., Murray, C., Rudan, I., Salomon, J., Simpson, P., Vos, T., Welch, V.: Guidelines for accurate and transparent health estimates reporting: the GATHER statement. The Lancet (2016)
31.
Garman, A.N., Tran, L.: Knowledge of the healthcare environment. J. Healthc. Manag. 51, 152–155 (2006)
Metadaten
Titel
Big Data Knowledge System in Healthcare
verfasst von
Gunasekaran Manogaran
Chandu Thota
Daphne Lopez
V. Vijayakumar
Kaja M. Abbas
Revathi Sundarsekar
Copyright-Jahr
2017
Buch
Internet of Things and Big Data Technologies for Next Generation Healthcare

Print ISBN: 978-3-319-49735-8

Electronic ISBN: 978-3-319-49736-5

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-49736-5_7