Designing a cloud based framework for healthcare system and applying clustering techniques for region wise diagnosis

Procedia Computer Science

Volumn 50, Issue , 2015, Pages 537-542

  Parekh, Maulik ^a   Saleena, B ^a  

^a VIT UNIVERSITY   (India)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; DIAGNOSIS; HEALTH CARE;

CLOUD-BASED; CLUSTERING TECHNIQUES; HEALTH CONDITION; HEALTH-CARE SYSTEM; KEY-SEGMENT;

BIG DATA;

EID: 84937407250     PISSN: None     EISSN: 18770509     Source Type: Conference Proceeding    
DOI: 10.1016/j.procs.2015.04.029     Document Type: Conference Paper

References (16)

1. P., Mell, T., Grance. The NIST definition of cloud computing [Online] , Available: Http: //csrc.nist.gov/groups/SNS/cloud computing/cloud-def. v15.doc, 2009. [Accessed: 15-July- 2011] .
2. L. Savu (2011) . Cloud Computing: Deployment Models, Delivery Models, Risks and Research Challenges, Computer and Management (CAMAN) , 2011 International Conference on, pp. 1-4.
3. P., Metri, G., Sarote (2011) .Privacy Issues and Challenges in Cloud Computing, International Journal of Advanced Engineering Sciences and Technologies (IJAEST) , vol. 5, pp.1-6.
4. IBM (2010) , Cloud Deployment and Delivery Models, Available from https: //www.ibm.com/developerworks/mydeveloperworks/c2028fdc [Accessed13- July -2011] .
5. Chenguang he, Xiaomao fan, Ye li (Jan 2013) ,Toward Ubiquitous Healthcare Services With a Novel Efficient Cloud Platform, Biomedical Engineering, IEEE Transactions on, Vol. 60, no. , pp. 230-234.
6. Ahn, Y.W.; Cheng, A.M.K.; Baek, J.; Jo, M.; Chen, H.-H (2013) . An auto-scaling mechanism for virtual resources to support mobile, pervasive, Realtime healthcare applications in cloud, Network, IEEE, Volume: 27, pp.: 62-6
7. Al Iqbal, R (2012) . Hybrid clinical decision support system: An automated diagnostic system for rural Bangladesh. Informatics, Electronics & Vision (ICIEV) , 2012 International Conference on, Page (s) : 76-81
8. Ilayaraja, M. ; Meyyappan, T. (2013) .Mining medical data to identify frequent diseases using Apriori algorithm, Pattern Recognition, Informatics and Mobile Engineering (PRIME) , 2013 International Conference on, Page (s) : 194-199.
9. Chauhan, R.; Kumar, A. (2013) , Cloud computing for improved healthcare: Techniques, potential and challenges, E-Health and Bioengineering Conference (EHB) , 2013, Page (s) : 1-4
10. Huang, Feixiang ; Wang,Shengyong ; Chan,Chien- Chung (2012) , Predicting disease by using data mining based on healthcare information system, Granular Computing (GrC) , 2012 IEEE International Conference on, Page (s) : 191-19
11. Chew, S.H.; Biomed. Eng.Res.Centre,Nanyang Technol.Univ.; Chong, P.A.; Gunawan, E.; Goh, K.W.,A Hybrid Mobile-based Patient Location Tracking System for Personal Healthcare Applications, Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE, Page (s) : 5188-5191, Aug. 30 2006-Sept. 3 2006
12. Yeo Sy Mey; Dept. of Comput. & Inf. Syst., Inst. Teknol .Brunei, Gadong, Brunei; Sankaranarayanan, S., Near Field Communication Based Patient Appointment, Cloud & Ubiquitous Computing & Emerging Technologies (CUBE) , 2013 International Conference on ,Page (s) : 98-103
13. Xueying Wu; Inf. Sci. & Eng. Coll., Dalian Polytech. Univ.,Dalian,China
14. Chunlong Yao,Application of improved K-means clustering algorithm in transit data collection, Biomedical Engineering and Informatics (BMEI) , 2010 3rd International Conference on (Volume: 7) ,Page (s) : 3028-3030
15. Poteras, C.M.; Fac. of Autom. Comput. & Electron., Univ. of Craiova, Craiova, Romania
16. Mihaescu, M.C. ; Mocanu, M. ,An optimized version of the K-Means clustering algorithm, Computer Science and Information Systems (FedCSIS) , 2014 Federated Conference on, Page (s) : 695-699