AI and neuron network-based computation method for cardiovascular data and related computation problems

Mingyong Zhou; Jiajin Li

doi:10.1117/12.3016679

15 January 2024 AI and neuron network-based computation method for cardiovascular data and related computation problems

Mingyong Zhou, Jiajin Li

Proceedings Volume 12983, Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023); 1298304 (2024) https://doi.org/10.1117/12.3016679
Event: Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023), 2023, Wuhan, China

Abstract

In this paper, starting from heart cardiovascular data of human beings, we provide a neuron network based mathematical computation method to capture the nonlinear dynamics of cardiovascular data and proposed an AI based approach to predict cardiovascular data and then classify between a healthy data model and an ill data model. From the cardiovascular nonlinear dynamics model, we further elucidate its similarity to Wiener problem as a special case and Kalman filtering. This clarify interpret able of AI and neuron network based approach for heartbeat data science.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mingyong Zhou and Jiajin Li "AI and neuron network-based computation method for cardiovascular data and related computation problems", Proc. SPIE 12983, Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023), 1298304 (15 January 2024); https://doi.org/10.1117/12.3016679

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available