Machine Learning Based Medicinal Care in Cloud
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2017 by IJCTT Journal|
|Year of Publication : 2017|
|Authors : Nandita Sengupta, Ramya chinnasamy|
|DOI : 10.14445/22312803/IJCTT-V47P135|
Nandita Sengupta, Ramya chinnasamy "Machine Learning Based Medicinal Care in Cloud". International Journal of Computer Trends and Technology (IJCTT) V47(4):219-226, May 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
The cloud computing is the emerging technology with benefits like reduced investment and maintenance cost, increased scalability, availability and reliability. With the characteristics of ubiquitous access, on-demand access, pay-per-use service and resiliency, the cloud computing is applied everywhere. Due to non-availability of specialists in primary health centers in developing and under developing countries, patients are not treated properly. In this paper, treatment model for treating the patients in primary health center has been suggested. This model is built on machine learning system, where IaaS, SaaS, PaaS based cloud computing contribute a lot. Data like symptoms and prescribed medicines for different diseases are collected by different hospitals and various research centers. Same data will be stored in cloud and for similar types of symptoms; medicines can be prescribed whenever required. Thus, in our suggested treatment model, machine learning will help in treating the patients with stored knowledge of specialists through cloud computing.
 Velte, “Cloud Computing-A Practical Approach,” Tata McGraw-Hill Edition
 Barrie Sosinsky ,”Cloud Computing Bible, “Wiley Publishing Inc.
 Thomas Erl / Ricardo Puttini / ZaighamMahmood, “Cloud Computing:Concepts, Technology & Architecture,” Prentice Hall
 Cloud computing: Benefits, risks and recommendations for information security,www.enisa.europa.eu/actyrm/files/deliverables/cloud-computing-risk-assessment/atdownload/fullReport/
 IDC, "IDC Ranking of issues of Cloud Computing model," http://blogs.idc.com/ie/?p=730/.
 Mohd Muntjir1 , Mohd. Junedul haque ,”Cloud Database Infrastructure: Database System Transference in Cloud Computing Management and Security “,International Journal of Computer Trends and Technology (IJCTT) – Volume 47 Number 1 May 2017
 Tariq Alwada , Omar Al-Zitawi , Jalal Omer Atoum,” Cloud Computing: Privacy, Mobility and Resources Utilization” , International Journal of Computer Trends and Technology (IJCTT) – Volume 41 Number 1 – November 2016
 Ibrahim Abaker Targio Hashem , Ibrar Yaqoob , Nor Badrul Anuar ,2014,” THE RISE OF BIG DATA ON CLOUD COMPUTING: REVIEW AND OPEN RESEARCH ISSUES”, ELSEVIER,Information Systems 47 (2015) 98–115
 S. Sivagowry, M. Durairaj,” A Study on the accessible techniques to classify and predict the risk of Cardio Vascular Disease”, International Journal of Computer Trends and Technology (IJCTT) – Volume 32 Number 1 - February 2016
 K. Vivekanand, A. Mohan, K.V.S. Sarma,” Study of the structure and functioning of referral mechanism of patients receiving treatment and records linkage under Revised National Tuberculosis Control Programme (RNTCP) of Government of India”, Indian Journal of Tuberculosis, Volume 64, Issue 2 pp. 69-150 ,April 2017.
 Gao Huang, Shiji Song, Jatinder N. D. Gupta , Cheng Wu,”Semi-Supervised and Unsupervised Extreme Learning Machines”, IEEE Transactions on Cybernetics,Volume: 44 Issue: 12, 12 March 2014.
 Chandra Sekhar Reddy , Bhanu Sreekar Reddy Karumuri,” Age Classification with Motif Shape Patterns on Local Binary Pattern”, International Journal of Computer Trends and Technology (IJCTT) – Volume 39 Number 3 - September2016
 S.P.Washimkar , S.D.Chede,” Comparative Analysis of Different Classifiers to Detect the Disease in Brain MRI Images”, International Journal of Computer Trends and Technology (IJCTT) – Volume 39 Number 1 - September2016.
 Balaji Krishnapuram, Lawrence Carin, Ma´rio A.T. Figueiredo, Alexander J. Hartemink,”Sparse Multinomial Logistic Regression:Fast Algorithms and Generalization Bounds” IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 27, Issue: 6,June 2005.
 Kuntal Barua , Prasun Chakrabarti,”Detection and Classification for Blood Cancer – A Survey “,International Journal of Computer Trends and Technology (IJCTT) – Volume 36 Number 2 - June 2016 ISSN: 2231-2803.
 Ana M. Gonzalez , Francisco J. Azuaje, Jose L. Ramirez, Jose F. da Silveira , Jose R. DorronsoroMachine Learning Techniques for the Automated Classification of Adhesin-Like Proteins in the Human Protozoan Parasite Trypanosoma cruzi”, IEEE/ACM Transactions on Computational Biology and Bioinformatics Volume: 6 Issue: 4,December 2008.
 Dong Huang , Ricardo Cabral, Fernando De la Torre,” Robust Regression”, IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 38, Issue: 2, Feb. 1 2016)
 G.K.Bhaskar,C.Imthyaz Sheriff,G.K.Sandhia” Detection and Exploitation of Heart bleed Vulnerability in Open SSL”, International Journal of Computer Trends and Technology (IJCTT) – Volume 34 Number 2 - April 2016 ISSN: 2231-2803
 Easton Li Xu, Xiaoning Qian, Tie Liu, Shuguang Cui,”Pairwise interaction analysis of logistic regression models”, IEEE Global Conference on Signal and Information Processing (GlobalSIP), Pages: 187 – 191, 2016.
 Yaoqing Yang, Pulkit Grover, Soummya Kar,”Fault-tolerant distributed logistic regression using unreliable components”, 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Pages: 940 – 947,2016.
Cloud computing, Data, Knowledge, Machine Learning, Specialists, Symptoms;