Vol. 3 No. 2 (2023): Journal of Deep Learning in Genomic Data Analysis
Articles

Real-Time AI-Powered Platforms for Managing Patient Rehabilitation Programs

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  • Dr. Felipe Bustamante
Dr. Felipe Bustamante
Associate Professor of Industrial Engineering, University of Santiago de Chile
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Published 05-11-2023

Keywords

  • Patient Rehabilitation
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Felipe Bustamante, “Real-Time AI-Powered Platforms for Managing Patient Rehabilitation Programs”, Journal of Deep Learning in Genomic Data Analysis, vol. 3, no. 2, pp. 72–86, Nov. 2023, Accessed: Nov. 14, 2024. [Online]. Available: https://thelifescience.org/index.php/jdlgda/article/view/51

Abstract

Patient rehabilitation is essential due to the high rate of injuries, both temporary and chronic, in everyday life. There is a significant market gap related to both disease and therapy management capabilities of existing applications currently used. Therefore, there is a growing trend in the search for technological platforms for rehabilitation from computer science perspectives, using sensors and computing algorithms to manage patient therapies. These platforms should allow the user to define, manage, and monitor multiple rehabilitation sessions, with support and detailed guidance, helping their recovery and improving their lifestyle. Furthermore, the industrial point of view is also of great importance, due to the composition of the current industry being mainly small and medium-sized companies. The use of projects and technological consortiums financed by the government allows companies that do not have specialization in the area to invest in technological development.

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