A review on personalized medicine technique using cognitive computing
Personalized Medicine is an important strategy for disease diagnosis and pre-care. This approach considers his/her personal data, circumstances, and genes to cure the disease. This method allows physicians and researchers to prognosticate the medication and prevent policies for appropriate viruses. The concept of cognitive computing works like a human brain to analyze and process the data. This method includes an automated system for using natural language processing, pattern recognition, and data mining to simulate how the human brain works. In this review, the synthesized overview of the current status of research on personalized medicine and how to address personalized medicine, using cognitive computing, are discussed. In addition, the national and international status of the research and issues, regarding personalized medicine, are presented.
 Po-Yen Wu et al."â€“Omic and Electronic Health Record Big Data Analytics for Precision Medicine", IEEE Transactions on Biomedical Engineering, ISSN: 0018-9294, 64(2), January 2017.
 Milad Zafar Nezhad et al."SAFS: A deep feature selection approach for precision medicine", 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), ISBN: 978-1-5090-1611-2, 15-18 Dec. 2016.
 Binhua Tang,"Toward optimization-oriented NGS peak alignment within the context of Precision Medicine Initiative", 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), ISBN: 978-1-5090-1611-2, 19 January 2017.
 Tien-En Chenet al. "S1 and S2 Heart Sound Recognition Using Deep Neural Networks", IEEE Transactions on Biomedical Engineering, ISSN: 0018-9294, 64(2), Feb. 2017.
 Mi Li et al. "Applications of Micro/Nano Automation Technology in Detecting Cancer Cells for Personalized Medicine", IEEE Transactions on Nanotechnology, ISSN: 1536-125X, 12(99), 17 January 2017.
 Raziur Rahman et al., "A mathematical framework for analyzing drug combination toxicity for personalized medicine applications",Healthcare Innovation Point-Of-Care Technologies Conference (HI-POCT), 2016 IEEE, ISBN: 978-1-5090-1166-7, 29 December 2016.
 Jennifer Berglund et al. "Women's Health Is Personal: More technologies by and for women are moving into the mainstream--thanks, in part, to personalized medicine", IEEE Pulse, ISSN: 2154-2287, 17 November 2016.
 Clyde F. Phelixe et al."Integrating information on genomics, transcriptomics, proteomics, and metabolomics into biosimulations for individualized personalized medicine", 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 24-27 Feb. 2016. https://doi.org/10.1109/BHI.2016.7455897.
 L.J. Lesko, â€œPersonalized Medicine: Elusive Dream or Imminent Reality?â€ Clinical Pharmacology & Therapeutics 81, pp. 807-816, June 2007.
 Topol EJ. Transforming medicine via digital innovation. Sci Transl Med 2010. https://doi.org/10.1126/scitranslmed.3000484.
 Powsner SM, Tufte ER. Graphical summary of patient status. Lan-cet, 344:386â€“389, 1994. https://doi.org/10.1016/S0140-6736(94)91406-0.
 Hood L, Heath JR, Phelps ME, Lin B. Systemâ€™s biology and new echnologies enable predictive and preventative medicine. Science, 306:640â€“643, June 2007. https://doi.org/10.1126/science.1104635.
 Yang JY, Yang MQ, Arabnia HR, Deng Y. Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are syner-gistic components of translational medicine and personalized healthcare research. BMC Genomics 9(2), 2008.
 Steinhubl SR, Muse ED, Topol EJ. Can mobile health technologies transform health care? JAMA, 310:2395â€“2396, 2005. https://doi.org/10.1001/jama.2013.281078.
 Diamandis EP. Biomarker validation is still the bottleneck in biomarker research. J Intern Med, 272:620, 2012. https://doi.org/10.1111/j.1365-2796.2012.02579.x.
 National Research Council (US) Committee on a Framework for Developing a New Taxonomy of Disease. Toward precision medi-cine: building a knowledge network for biomedical research and a new taxonomy of disease. Washington, DC: National Academies Press, 2011.
 Gandikota Ramu and B.Eswara Reddy Mobile Cloud-Based Approach for Disease Diagnosis. I-managerâ€™s Journal on Cloud Computing., 1(3), Print ISSN 2349-6835, E-ISSN 2350-1308, pp. 21-28, 2014.
 Gandikota Ramu and B.Eswara Reddy, â€œSecure architecture to manage EHRâ€™s in cloud using SSE and ABEâ€, International Journal of Health and Technology, Springer, ISSN: 2190-7188 pp. 195-205, Volume 5, Issue 3-4, December 2015.
 S. Naisha Sultana, B. Eswara Reddy and Gandikota Ramu "Cloud-Based Development of Smart and Connected Data in Healthcare Application".International Journal of Distributed and Parallel Systems (IJDPS) Vol.5, No.6, November 2014.
 Gandikota Ramu et al., â€œA Review on Precision Medicine and Its Advantagesâ€, Pak. J. Biotechnology, Vol. 14 (3), October 2017.
 Gandikota Ramu, â€œEnhancing Medical Data Security in the Cloud Using RBAC-CPABE and ASSâ€, International Journal of Applied Engineering Research ISSN 0973-4562 Volume 13, Number 7 (2018) pp. 5190-5196.
 Gandikota Ramu, â€œA secure cloud framework to share EHRs using modified CP-ABE and the attribute bloom filterâ€, (Springer) Education and Information Technology, https://doi.org/10.1007/s10639-018-9713-7.http://www.ndtv.com/india-news/over-20-percent-of-indians-suffer-from-chronicdiseases-report-1470031