Intelligent decision support systems for dementia care: A scoping review

被引：6

作者：

Andargoli, Amirhossein Eslami ^{[1
,2
]}

Ulapane, Nalika ^{[2
]}

Nguyen, Tuan Anh ^{[1
,3
]}

Shuakat, Nadeem ^{[2
]}

Zelcer, John ^{[2
]}

Wickramasinghe, Nilmini ^{[2
,4
]}

机构：

[1] Swinburne Univ Technol, Melbourne, Australia

[2] La Trobe Univ, Melbourne, Australia

[3] Natl Ageing Res Inst, Parkville, Australia

[4] Epworth HealthCare, Richmond, Australia

来源：

ARTIFICIAL INTELLIGENCE IN MEDICINE | 2024年 / 150卷

关键词：

Artificial intelligence; Decision support systems; Analytics; Dementia; Alzheimer; ALZHEIMERS-DISEASE; COGNITIVE IMPAIRMENT; DIAGNOSIS; CLASSIFICATION; REPRESENTATION;

D O I：

10.1016/j.artmed.2024.102815

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the context of dementia care, Artificial Intelligence (AI) powered clinical decision support systems have the potential to enhance diagnosis and management. However, the scope and challenges of applying these technologies remain unclear. This scoping review aims to investigate the current state of AI applications in the development of intelligent decision support systems for dementia care. We conducted a comprehensive scoping review of empirical studies that utilised AI-powered clinical decision support systems in dementia care. The results indicate that AI applications in dementia care primarily focus on diagnosis, with limited attention to other aspects outlined in the World Health Organization (WHO) Global Action Plan on the Public Health Response to Dementia 2017-2025 (GAPD). A trifecta of challenges, encompassing data availability, cost considerations, and AI algorithm performance, emerges as noteworthy barriers in adoption of AI applications in dementia care. To address these challenges and enhance AI reliability, we propose a novel approach: a digital twin-based patient journey model. Future research should address identified gaps in GAPD action areas, navigate data-related obstacles, and explore the implementation of digital twins. Additionally, it is imperative to emphasize that addressing trust and combating the stigma associated with AI in healthcare should be a central focus of future research directions.

引用

页数：12

共 73 条

[11] Deep learning and image processing-based early detection of Alzheimer disease in cognitively normal individuals [J].

Borkar, Pradnya ;

Wankhede, Vishal Ashok ;

Mane, Deepak T. ;

Limkar, Suresh ;

Ramesh, J. V. N. ;

Ajani, Samir N. .

SOFT COMPUTING, 2023, 28 (Suppl 2) :637-637

[12] Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm [J].

Bruynseels, Koen ;

de Sio, Filippo Santoni ;

van den Hoven, Jeroen .

FRONTIERS IN GENETICS, 2018, 9

[13] A hybrid machine learning approach for prediction of conversion from mild cognitive impairment to dementia [J].

Bucholc, Magda ;

Titarenko, Sofya ;

Ding, Xuemei ;

Canavan, Callum ;

Chen, Tianhua .

EXPERT SYSTEMS WITH APPLICATIONS, 2023, 217

[14] A practical computerized decision support system for predicting the severity of Alzheimer's disease of an individual [J].

Bucholc, Magda ;

Ding, Xuemei ;

Wang, Haiying ;

Glass, David H. ;

Wang, Hui ;

Prasad, Girijesh ;

Maguire, Liam P. ;

Bjourson, Anthony J. ;

McClean, Paula L. ;

Todd, Stephen ;

Finn, David P. ;

Wong-Lin, KongFatt .

EXPERT SYSTEMS WITH APPLICATIONS, 2019, 130 :157-171

[15] Interpretable Clinical Decision Support System for Audiology Based on Predicted Common Audiological Functional Parameters (CAFPAs) [J].

Buhl, Mareike .

DIAGNOSTICS, 2022, 12 (02)

[16] Sources of bias in artificial intelligence that perpetuate healthcare disparities-A global review [J].

Celi, Leo Anthony ;

Cellini, Jacqueline ;

Charpignon, Marie-Laure ;

Dee, Edward Christopher ;

Dernoncourt, Franck ;

Eber, Rene ;

Mitchell, William Greig ;

Moukheiber, Lama ;

Schirmer, Julian ;

Situ, Julia ;

Paguio, Joseph ;

Park, Joel ;

Wawira, Judy Gichoya ;

Yao, Seth .

PLOS DIGITAL HEALTH, 2022, 1 (03)

[17] Effective diagnosis of Alzheimer's disease by means of large margin-based methodology [J].

Chaves, Rosa ;

Ramirez, Javier ;

Gorriz, Juan M. ;

Illan, Ignacio A. ;

Gomez-Rio, Manuel ;

Carnero, Cristobal .

BMC MEDICAL INFORMATICS AND DECISION MAKING, 2012, 12

[18] The Evaluation of a Compassion-Focused Therapy Group for Couples Experiencing a Dementia Diagnosis [J].

Collins, Rebecca N. ;

Gilligan, Liam J. ;

Poz, Rebecca .

CLINICAL GERONTOLOGIST, 2018, 41 (05) :474-486

[19] Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus [J].

Colliot, Olivier ;

Chetelat, Gael ;

Chupin, Marie ;

Desgranges, Beatrice ;

Magnin, Benoit ;

Benali, Habib ;

Dubois, Bruno ;

Garnero, Line ;

Eustache, Francis ;

Lehericy, Stephane .

RADIOLOGY, 2008, 248 (01) :194-201

[20] Application of Machine Learning in Postural Control Kinematics for the Diagnosis of Alzheimer's Disease [J].

Costa, Luis ;

Gago, Miguel F. ;

Yelshyna, Darya ;

Ferreira, Jaime ;

Silva, Helder David ;

Rocha, Luis ;

Sousa, Nuno ;

Bicho, Estela .

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2016, 2016

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