loading page

Advanced Cardiovascular Health in a Quantum AI-driven Healthcare Framework
  • Sarvapriya M Tripathi,
  • Himanshu Upadhyay,
  • Jayesh Soni
Sarvapriya M Tripathi
Electrical and Computer Engineering, Florida International University Miami

Corresponding Author:[email protected]

Author Profile
Himanshu Upadhyay
Electrical and Computer Engineering, Florida International University Miami
Jayesh Soni
Electrical and Computer Engineering, Florida International University Miami

Abstract

With the advent of Healthcare 4.0, there is increased interest from researchers the world over in the application of modern, cutting-edge Artificial Intelligence (AI) and Quantum Artificial Intelligence (QAI) algorithms in solving healthcare challenges. The era of Quantum Computing (QC) promises to bring significant advancements in several areas of healthcare such that it may be sensible to give this hybrid Quantum/Classical paradigm its own name-Healthcare4Q. The potential of QC will extend the reach of Healthcare4Q with the help of diverse technologies such as quantum-enabled wearables, quantum-secure transfer and storage of data, and quantum computing at edge, fog, and cloud. All of these technologies promise to catapult Healthcare4Q to become the most capable healthcare framework in the advancement of medical innovations and improvement of patient care. An integral part of a person's health lies in cardiovascular health, and thus prioritizing and optimizing cardiovascular health remains vital to the broader goals of public health and healthcare sustainability. In this study, under the paradigm of Healthcare4Q, we propose a framework called the Quantum AIdriven Heart Health Framework (QAIHHF) that can provide advanced predictive intelligence to healthcare providers by utilizing historical and real-time data and processing capabilities proposed in Healthcare4Q. We show that when applied to various diagnostics and health indicators such as ECG data, the Quantum AI provides accuracy at a level equal to or higher as compared to the classical methods thus proving itself to be the critical component that will herald the era of Healthcare4Q.
02 Apr 2024Submitted to TechRxiv
02 Apr 2024Published in TechRxiv