Markov mathematical analysis for comprehensive real-time data-driven in healthcare

Sudhakar Sengan; Ganga Rama Koteswara Rao; Osamah Ibrahim Khalaf; M. Rajesh Babu

Sudhakar Sengan Department of Computer Science and Engineering, PSN College of Engineering and Technology, Tirunelveli â€“ 627152, Tamil Nadu, India
Ganga Rama Koteswara Rao epartment of Computer Science {\&} Engineering Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India
Osamah Ibrahim Khalaf Al-Nahrain University-Baghdad, Iraq, AlNahrain Nanorenewable Energy Research Centre
M. Rajesh Babu Department of Computer Science and Engineering, RVS College of Engineering and Technology, Coimbatore, Tamil Nadu, India

Abstract

This study explores how mobile healthcare technologies can develop business growth for Indian life and health insurance companies. It examines how insurance firms can integrate non-traditional but potentially valuable data. Data and research have become more and more complicated and need processing and demonstrable review to achieve the flexibility required within the company, the study says. The study uses online data search data to evaluate risk assessment using a multinational probabilistic approach and multiple linear regression by Markov Mathematical Analysis. The case study for primary qualitative research and interpretation is used in the sample health insurance business in India. Health applications can potentially affect patient appointments and relationships. Health technologies have the underlying potential to aid with the prevention of infectious diseases. Big data promise they exist, such as identifying development about the insurers' collectivity.