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Review Article Open Access December 27, 2022

Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements

Kiran Kumar Maguluri 1,*, Chandrashekar Pandugula 2, Srinivas Kalisetty 3 and Goli Mallesham 4
1
IT systems Architect, Cigna Plano Texas, USA
2
Sr Data Engineer, Lowes Inc NC, USA
3
Integration and AI lead, Miracle Software Systems, USA
4
Research Assistant, USA
Publihed in: Current Research in Public Health (Volume 2, Issue 1, 2022)
Page(s): 112-126
DOI: 10.31586/jaibd.2022.1201
Received
August 11, 2022
Revised
October 16, 2022
Accepted
December 21, 2022
Published
December 27, 2022
Keywords
Chronic Pain; Acute Pain; Pain Management; Veterans; Aging Population; Athletic Population; Working Population; Under-Reporting; Predictive Analytics; Opioid Use; Post-Operative Pain; Real-Time Feedback; Neural Networks; Personalized Pain Management; Goal Setting; Longitudinal Data; Electrical Simulations; Clinical Care Gap; Discharge to Normal Function; Personalized Treatment
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2022. Published by Scientific Publications
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Cite This Article

APA Style
Maguluri, K. K. , Maguluri, K. K. Pandugula, C. , Pandugula, C. Kalisetty, S. , & Kalisetty, S. (2022). Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements. Current Research in Public Health, 2(1), 112-126. https://doi.org/10.31586/jaibd.2022.1201
ACS Style
Maguluri, K. K. ; Maguluri, K. K. Pandugula, C. ; Pandugula, C. Kalisetty, S. ; Kalisetty, S. Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements. Current Research in Public Health 2022 2(1), 112-126. https://doi.org/10.31586/jaibd.2022.1201
Chicago/Turabian Style
Maguluri, Kiran Kumar, Kiran Kumar Maguluri. Chandrashekar Pandugula, Chandrashekar Pandugula. Srinivas Kalisetty, and Srinivas Kalisetty. 2022. "Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements". Current Research in Public Health 2, no. 1: 112-126. https://doi.org/10.31586/jaibd.2022.1201
AMA Style
Maguluri KK, Maguluri KKPandugula C, Pandugula CKalisetty S, Kalisetty S. Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements. Current Research in Public Health. 2022; 2(1):112-126. https://doi.org/10.31586/jaibd.2022.1201 
@Article{crph1201,
AUTHOR = {Maguluri, Kiran Kumar and Pandugula, Chandrashekar and Kalisetty, Srinivas and Mallesham, Goli},
TITLE = {Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements},
JOURNAL = {Current Research in Public Health},
VOLUME = {2},
YEAR = {2022},
NUMBER = {1},
PAGES = {112-126},
URL = {https://www.scipublications.com/journal/index.php/JAIBD/article/view/1201},
ISSN = {2831-5162},
DOI = {10.31586/jaibd.2022.1201},
ABSTRACT = {There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare appointments and hospital settings. In this review, the current gap in clinical care for real-time feedback and guidance with pain management decision-making for chronic and post-operative pain treatment is defined. We examine the recent and future applications for predictive analytics of opioid use after surgery and implementing real-time neural networks for personalized pain management goal setting for particular individuals on the path to discharge to normal function. Integration of personalized neural networks with longitudinal data may enable the development of future treatment personalizations paired with electrical simulations.},
}
%0 Journal Article
%A Maguluri, Kiran Kumar
%A Pandugula, Chandrashekar
%A Kalisetty, Srinivas
%A Mallesham, Goli
%D 2022
%J Current Research in Public Health

%@ 2831-5162
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%N 1
%P 112-126

%T Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements
%M doi:10.31586/jaibd.2022.1201
%U https://www.scipublications.com/journal/index.php/JAIBD/article/view/1201

TY  - JOUR
AU  - Maguluri, Kiran Kumar
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AB  - There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare appointments and hospital settings. In this review, the current gap in clinical care for real-time feedback and guidance with pain management decision-making for chronic and post-operative pain treatment is defined. We examine the recent and future applications for predictive analytics of opioid use after surgery and implementing real-time neural networks for personalized pain management goal setting for particular individuals on the path to discharge to normal function. Integration of personalized neural networks with longitudinal data may enable the development of future treatment personalizations paired with electrical simulations.
DO  - Advancing Pain Medicine with AI and Neural Networks: Predictive Analytics and Personalized Treatment Plans for Chronic and Acute Pain Managements
TI  - 10.31586/jaibd.2022.1201
ER  -