ARTIFICIAL INTELLIGENCE AND BIG DATA ANALYTICS IN HEALTHCARE FOR PREDICTIVE ANALYSIS AND FUTURE PROSPECTS

Received: 13.06.2021; Revised: 22.07.2021, Accepted: 31.08.2021, Published Online: 09.09.2021

Sushama Rani Dutta

Assistant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad – 500075, sushamadutta@klh.edu.in

Dr. TVS Sriram

Associate Professor, Dept of CSE NSRIT (Nadimpalli Satyanarayana Institute of Technology) –Autonomous, Visakhapatnam, tvssriram.cse@nsrit.edu.in

Kishore Balasubramanian

Assistant Professor, EEE, Dr Mahalingam College of Engineering and Technology

Pollachi – 642001, bkishore1979@gmail.com

Ms. Sneha S Bagalkot

Assistant Professor, Department of CSE, Presidency University, Itgalpura, Bangalore – 560064, snehasbagalkot@presidencyuniversity.in

Dr. Madhavi Kolukuluri

Associate Professor, Dept of CSE NSRIT (Nadimpalli Satyanarayana Institute of Technology) –Autonomous, Visakhapatnam, kolukulurimadhavi@gmail.com

Abstract

Big data is huge volume of storage which can be wonderful. For the previous two centuries, it’s become a subject of significant benefit because of its enormous potential. Multiple sources of big data are health facility records, medical information and outcomes from medical exams in the healthcare sector. Big data analytics can improve the quality of care, promote and personalize clinical outcomes, enhancing treatment interactions and ultimately reduce expenditures. Big data helps us discover and reimaging a lot of fields which are not restricted to learning, health and legislation. In order to promote treatment options, AI in medical services needed real, overarching framework and customized perspectives for medical professionals. This paper will demonstrate that predictive analysis methods in the healthcare sector are important for AI and Big Data Analytics. The technology will collect valuable insights, through sophisticated project planning and Big Data processing, which will aid in judgment and patient monitoring in real-time. This paper examines the application of KNN in the heart disease diagnosis for medical practitioners. The main purpose of this paper is to provide artificial intelligence and large-scale data assessment for prediction and opportunities in medical care.

Keywords: Big data analytics, Artificial intelligence, Health care, predictive analytics, KNN