[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122497-en":3,"doc-seo-122497-105":29,"detail-sidebar-cat-0-en-105":89},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":11},122497,687197207919,"Theodora","https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552",8,"Research & Report","Identifying Key Factors Associated with Assistive Technology Availability for Dementia Care Using Machine Learning","This study explores factors influencing the availability of assistive technology for people with dementia by applying machine learning to global health indicators. Using WHO Global Health Observatory (GHO) OData data from 62 countries and 200 predictors, the analysis processed missingness and trained a random forest model with 10-fold cross-validation and hyperparameter tuning. Key factors identified include carer support services, protective legislation, and access to reimbursable products, alongside related financial and psychosocial resources. Results show strong predictive performance and support targeted resource and policy planning to improve dementia care infrastructure.","Edith Cowan University  \nResearch Online  \nResearch outputs 2022 to 2026  \n5-15-2025  \nIdentifying key factors associated with assistive technology availability for dementia care using machine learning  \nWai Hang Kwok Edith Cowan University  \nSyed Afaq Ali Shah Edith Cowan University  \nGuanjin Wang  \nFollow this and additional works at: [https://ro.ecu.edu.au/ecuworks2022-2026](https://ro.ecu.edu.au/ecuworks2022-2026)  \n Part of the Neurosciences Commons  \n10.3233/SHTI250592  \nKwok, W. H., Shah, S. A. A., & Wang, G. (2025) . Identifying key factors associated with assistive technology availability for dementia care using machine learning. Studies in Health Technology and Informatics, 327, 1242-1243. [https://doi.org/10.3233/SHTI250592](https://doi.org/10.3233/SHTI250592)  \n[This Journal Article is posted at Research Online.](This Journal Article is posted at Research Online.)[ ](This Journal Article is posted at Research Online.)[https://ro.ecu.edu.au/ecuworks2022-2026/6360](https://ro.ecu.edu.au/ecuworks2022-2026/6360)  \n1242  \nIntelligent Health Systems – From Technology to Data and Knowledge  \nE. Andrikopoulou et al. (Eds.)  \n© 2025 The Authors.  \nThis article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).  \ndoi:10.3233/SHTI250592  \nIdentifying Key Factors Associated with Assistive Technology Availability for Dementia Care Using Machine Learning  \nWai Hang KWOKa,1, Syed Afaq Ali SHAHa, and Guanjin WANG ba Edith Cowan University, Western Australia  \nb Murdoch University, Western Australia  \nORCiD ID: Wai Hang KWOK [https://orcid.org/0000-0002-1854-4300](https://orcid.org/0000-0002-1854-4300), Syed Afaq Ali SHAH [https://orcid.org/0000-0003-2181-8445](https://orcid.org/0000-0003-2181-8445), Guanjin WANG [https://orcid.org/0000-0002-5258-0532](https://orcid.org/0000-0002-5258-0532)  \nAbstract. This study explores the factors influencing the availability of assistive technology for people with dementia through the application of machine learning.  \nThe analysis identified key factors, including carer support, protective legislation, and access to reimbursable products from the WHO Global Health Observatory. A random forest model with high accuracy emphasises the importance of targeted  \nresources and policies in improving dementia care infrastructure.  \nKeywords. Assistive technology, dementia care, machine learning, prediction  \nmodel, variable importance analysis  \n1. Introduction  \nThe availability of assistive technology for people with dementia is shaped by key factors, including the presence of national and local non-governmental organisations (NGOs) that facilitate access to services and support [1]. NGOs involved in policy development, supported by government funding, also play a crucial role. Implementation of carer support, financial benefits, and dementia-friendly initiatives further improves access. Additionally, psycho-social supports, respite care, and dementia training from NGOs or public sectors enhance the broader dementia care ecosystem, improving access to technology. This study aimed to explore factors influencing the availability of assistive technology for people with dementia.  \n2. Methods  \nThis study used the WHO Global Health Observatory (GHO) OData API to extract indicators containing the term “dementia” in 2017 [2] . Data from 62 countries and 200 predictors were processed using R, involving filtering predictors with ≤ 30% missing data, and handling of missing values through techniques like K-Nearest Neighbours (KNN) imputation. A machine learning framework with 10-fold cross-validation and  \n1 Corresponding Author: Wai Hang Kwok; [E-mail: w.kwok@ecu.edu.au](E-mail: w.kwok@ecu.edu.au).  \nW.H. Kwok et al. / Identifying Key Factors Associated with Assistive Technology Availability 1243  \nhyperparameter tuning was developed using the caret package in R [3], training a random forest model on ","cbCaiuB7Tig7VNey","https://ap.wps.com/l/cbCaiuB7Tig7VNey","pdf",197368,1,3,"English","en",105,"# Abstract\n# Introduction\n# Methods\n# Results\n# Discussion\n# Conclusions\n# References","[{\"question\":\"What is the main goal of this study?\",\"answer\":\"To identify key factors associated with the availability of assistive technology for people with dementia using machine learning.\"},{\"question\":\"What data and modeling approach were used?\",\"answer\":\"Indicators containing “dementia” from the WHO Global Health Observatory were extracted for 2017, then processed and modeled with a random forest using 10-fold cross-validation and hyperparameter tuning.\"},{\"question\":\"Which factors were found to be most important for assistive technology availability?\",\"answer\":\"Carer support services ranked highest, followed by protective laws, then availability of reimbursable hygiene products and housing adjustments.\"}]","Identifying Key Factors Associated with Assistive Technology Availability for Dementia Care Using Machine Learning | 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