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Automated screening of patients for dietician referral

Soomro, Kamran; Pimenidis, Elias

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Authors

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Dr Kamran Soomro Kamran.Soomro@uwe.ac.uk
Associate Professor of Artificial Intelligence



Contributors

L. Iliadis
Editor

P. Angelov
Editor

C. Jayne
Editor

Abstract

Critical Care Units (CCU) in a hospital treat the severely sick patients that need constant monitoring and close medical attention. Feeding patients, enteral feeding in particular, is a critical and continuous process. Monitoring patients, managing their feeding and referring to a dietician is a key factor in CCUs. Screening patients for referral to a dietician in a CCU is an error-prone and complicated task. One of the main challenges in this regard is that the data needed to screen patients is scattered among many different variables and textual forms. The number of patients being treated in the CCU is also a significant problem since it becomes difficult for the staff to keep track of the needs of all patients. Therefore, an automated screening tool can support effectively the feeding process and contribute considerably towards improving the quality and consistency of patient care. In this paper we present early stages of a project that aims at using machine learning techniques to help CCU consultants to automatically screen patients for dietician referral.

Citation

Soomro, K., & Pimenidis, E. (2020). Automated screening of patients for dietician referral. In L. Iliadis, P. Angelov, C. Jayne, & E. Pimenidis (Eds.), Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. https://doi.org/10.1007/978-3-030-48791-1_24

Conference Name EANN 2020 21st International Conference on Engineering Applications of Neural Networks
Conference Location Halkidiki, Greece
Start Date Jun 5, 2020
End Date Jun 7, 2020
Acceptance Date May 1, 2020
Online Publication Date May 28, 2020
Publication Date May 28, 2020
Deposit Date Sep 18, 2020
Publicly Available Date Mar 28, 2024
Series Title Proceedings of the International Neural Networks Society
Book Title Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference
ISBN 9783030487904
DOI https://doi.org/10.1007/978-3-030-48791-1_24
Public URL https://uwe-repository.worktribe.com/output/5973778

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