Abstract

Aim/Purpose

This work attempts to investigate the application of Long Short Term Memory (LSTM)-based predictive analytics in the medical field. The scope comprises the development and application of LSTM models to forecast outcomes, including patient diagnosis, treatment responses, healthcare resource consumption, and other relevant variables.

Details

Title
Enhancing Healthcare Industrial Applications With LSTM-Based Predictive Analytics
Author
Sushama, C; Shaik Mohammad Rafee  VIAFID ORCID Logo  ; Jha, Jaimala; Sujatha, S  VIAFID ORCID Logo  ; Jagadeesan Srinivasan; Mohana, Krishna I
First page
14
Publication year
2025
Publication date
2025
Publisher
Informing Science Institute
ISSN
15479684
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.28945/5416
ProQuest document ID
3179826333
Copyright
© 2025. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.