eprintid: 17384
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/73/84
datestamp: 2023-12-19 03:23:47
lastmod: 2023-12-19 03:23:47
status_changed: 2023-12-19 03:07:58
type: article
metadata_visibility: show
creators_name: Ibad, T.
creators_name: Abdulkadir, S.J.
creators_name: Aziz, N.B.A.
title: Evolving Spiking Neural Network for Prediction Problems in Healthcare System
ispublished: pub
keywords: Diagnosis; Intensive care units; Neural networks; Patient rehabilitation; Regression analysis, ESNN; Healthcare systems; Learning strategy; Neural-networks; Optimisations; Prediction problem; Regression; Regression problem, Forecasting
note: cited By 0; Conference of 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 ; Conference Date: 17 December 2020 Through 18 December 2020; Conference Code:286319
abstract: This paper highlights the role of evolving spiking neural networks (an enhanced version of SNN) for predicting medical diagnosis. This article aims to focus on regression problems under a supervised learning strategy. In this paper, we have trained and tested eSNN on benchmarking datasets. Among the three datasets, one is the ICU Dataset which helps in predicting the recovery ration of patients who stayed in ICU. Another dataset is PlasmaRetinol which predicts the risk of cancer-related to certain carotenoids. Dataset pharynx is a part of a study conducted in the USA to determine the success rate of two radiation types. The selected datasets are those which were previously used for BioMedical Engineering related tasks. Later the evaluation was conducted using Regression Metrics. From experiment results, it is concluded that eSNN with standard parameters without optimization performed well but there is still space available for improvement to achieve the highest possible prediction scores. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
date: 2022
publisher: Springer Science and Business Media Deutschland GmbH
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142736147&doi=10.1007%2f978-981-16-2183-3_60&partnerID=40&md5=29f25cc243b0e90b295d8add30500d59
id_number: 10.1007/978-981-16-2183-3₆₀
full_text_status: none
publication: Lecture Notes in Electrical Engineering
volume: 758
pagerange: 625-631
refereed: TRUE
isbn: 9789811621826
issn: 18761100
citation:   Ibad, T. and Abdulkadir, S.J. and Aziz, N.B.A.  (2022) Evolving Spiking Neural Network for Prediction Problems in Healthcare System.  Lecture Notes in Electrical Engineering, 758.  pp. 625-631.  ISSN 18761100