Approaches Based on Data for Personalized Medicine and Healthcare Analytics

Authors

  • Krishna Jayanth Rolla 5029 Havencrest Drive, Fort Mill, SC 29715
  • S. Shabana Begum Assistant Professor Computer Science and Engineering (Data Science), G. PULLA REDDY ENGINEERING COLLEGE (Autonomous) Kurnool Andhra Pradesh
  • Ashish Kumar Tamrakar Associate Professor, Computer Science and Engineering, RSR, Rungta College of Engineering & Technology, kurud, Bhilai Pincode- 490024, Durg Chhattisgarh
  • S. Satya Nagendra Rao Assistant Professor, CSE, St. Peter's Engineering College, Medchal-Malkajgiri, Hyderabad, Telangana

Keywords:

Big Data Analytics, Healthcare, Internet of Medical Things (IoMT), Precision Medicine, Machine Learning

Abstract

Massive data analytics has opened up revolutionary possibilities for the medical field by providing hitherto unseen insights into treatment of patients, decision-making procedures, and the streamlining of clinical workflows. In order to provide a thorough overview of the many uses and ramifications of analytics for big data for healthcare providers, this review generates recent literature. This research delves into the application of large-scale medical treatment datasets, the incorporation of the Worldwide Web of Medical Things (IoMT) to the sustainable development of smart cities, and the ongoing making decisions in healthcare institutions in the face of imperfect knowledge in the Big Data age. Furthermore, the review highlights the potential to feed innovation in these fields by examining the scope of uses for big data in the manufacturing, logistics, and healthcare industry sectors. It also explores Apache Spark's uses in the healthcare industry, highlighting how it advances advances based on data and boosts data processing effectiveness. The study goes on to show how precision medicine along with sophisticated data analysis can be used to optimize the clinical process and improve efficiency while personalizing healthcare delivery. Also examined are the creation of information about healthcare graphs, the relationship between blockchain and medical infrastructure, and the use of machine learning within the Internet of Conducts to feed individual medical applications. These topics provide light on the possibilities of these innovations for expressing knowledge, improved security, and tailored medical treatment. A comprehensive grasp of the revolutionary possibilities of data analysis in healthcare is made possible by the methodical investigation of these subjects. The literature assessment's collective perspectives lay the foundation for upcoming advancements, highlighting the necessity of ongoing study and creativity in utilizing data-driven strategies to achieve improved healthcare outcomes.

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Published

24.03.2024

How to Cite

Rolla, K. J. ., Begum, S. S. ., Tamrakar, A. K. ., & Rao, S. S. N. . (2024). Approaches Based on Data for Personalized Medicine and Healthcare Analytics. International Journal of Intelligent Systems and Applications in Engineering, 12(19s), 125–132. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5052

Issue

Vol. 12 No. 19s (2024)

Section

Research Article

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