Heart Disease Prognosis and Quick Access to Medical Data Record Using Data Lake with Deep Learning Approaches
Keywords:
Medical data, heart disease, retrieving, classification, prediction and similarity matchingAbstract
The prediction of heart diseases is necessary of this data as considerable mortality rate is hiked at global level. The Convolutional Neural Network (CNN) is then fed the segmented regions to get a disease classification. For security reasons, it's not a good idea to keep all of your medical records in one central spot. As a means to this end, the files can be partitioned according to certain criteria and then stored on the cloud. When many document divisions from various sources are submitted, this would obscure their connection to one another. Moreover, the security of medical records may be strengthened by integrating cryptography with splitting technique. Although the security of documents would be enhanced if they were divided and shared with two or more independent parties, it would be impossible to reconstruct the original papers from the distributed pieces without some way of knowing which pieces belonged. The proposed model provide a better performance than other comparing model.
Downloads
References
Khamis HS, Cheruiyot KW, Kimani S. Application of k-nearest neighbour classification in medical data mining. International Journal of Information and Communication Technology Research. 2014 Apr;4(4).
Manogaran G, Lopez D. Health data analytics using scalable logistic regression with stochastic gradient descent. International Journal of Advanced Intelligence Paradigms. 2018;10(1-2):118-32.
Tuli, S., Basumatary, N., Gill, S.S., Kahani, M., Arya, R.C., Wander, G.S. and Buyya, R., 2020. HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments. Future Generation Computer Systems, 104, pp.187-200.
Senthil R, Narayanan B, Velmurugan K. Develop the hybrid Adadelta Stochastic Gradient Classifier with optimized feature selection algorithm to predict the heart disease at earlier stage. Measurement: Sensors. 2023 Feb 1;25:100602.
Gonsalves AH, Thabtah F, Mohammad RM, Singh G. Prediction of coronary heart disease using machine learning: an experimental analysis. InProceedings of the 2019 3rd International Conference on Deep Learning Technologies 2019 Jul 5 (pp. 51-56).
Chakraborty C, Bhattacharya S. Healthcare data monitoring under Internet of Things. InGreen Computing and Predictive Analytics for Healthcare 2020 Dec 10 (pp. 1-18). Chapman and Hall/CRC.
Ahmed K, Singh S, Pathak C, Singh S. BIG DATA ANALYTICS FOR CHRONIC DISEASE PREDICTION.
Ross JS, Mulvey GK, Stauffer B, Patlolla V, Bernheim SM, Keenan PS, Krumholz HM. Statistical models and patient predictors of readmission for heart failure: a systematic review. Archives of internal medicine. 2008 Jul 14;168(13):1371-86.
Kurland LT, Molgaard CA. The patient record in epidemiology. Scientific American. 1981 Oct 1;245(4):54-63.
Li Y, Guo L, Guo Y. Enabling health monitoring as a service in the cloud. In2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing 2014 Dec 8 (pp. 127-136). IEEE.
Sagar. S.M and Dhaval. P. A Review of a Novel Decision Tree Based Classifier for Accurate Multi Disease Prediction. International Journal for Scientific Research & Development. 2015; 3(2): 240-244.
Sairabi. H.M and Devale. P.R. Prediction of Heart Disease using Modified K-means and by using Naive Bayes. International Journal of Innovative Research in Computer and Communication Engineering, 2015; 3(10): 10265-1027.
Shantakumar. B.P and Kumaraswamy. Y.S. Extraction of Significant Patterns from Heart Disease Warehouses for Heart Attack Prediction. International Journal of Computer Science and Network Security (IJCSNS), 2009; 9(2): 228-235.
Anbarasi. M, Anupriya. E, Iyengar. N.Ch.S.N. Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm. International Journal of Engineering Science and Technology, 2010; 2(10): 5370-5376.
Jyoti. S, Ujma. A, Dipesh. S, Sunita. S. Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction. International Journal on Computer Applications, 2011; 17(8): 43-48.
Subbalakshmi. G, Ramesh. K, Chinna Rao. M. Decision Support in Heart Disease Prediction System using Naive Bayes. Indian Journal of Computer Science and Engineering, 2011; 2(2): 170-176.
G. Quellec, M. Lamard, G. Cazuguel, B. Cochener and C. Roux “Wavelet optimization for content-based image retrieval in medical databases”, Medical Image Analysis, Vol. 14, pp. 227–241, 2010.
Jorge A. Ruiz-Vanoye, OcotlánDíaz-Parra, Felipe Cocón, Andrés Soto, “Meta- Heuristics Algorithms based on the Grouping of Animals by Social Behavior for the Traveling Salesman Problem”, International Journal of Combinatorial Optimization Problems and Informatics, Vol. 3, No. 3, pp. 104-123, Sep.-Dec. 2012
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
