Applications of artificial intelligence in dementia research.

Cambridge prisms, Precision medicine Pub Date : 2022-12-06 eCollection Date: 2023-01-01 DOI:10.1017/pcm.2022.10
Kelvin K F Tsoi, Pingping Jia, N Maritza Dowling, Jodi R Titiner, Maude Wagner, Ana W Capuano, Michael C Donohue
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Abstract

More than 50 million older people worldwide are suffering from dementia, and this number is estimated to increase to 150 million by 2050. Greater caregiver burdens and financial impacts on the healthcare system are expected as we wait for an effective treatment for dementia. Researchers are constantly exploring new therapies and screening approaches for the early detection of dementia. Artificial intelligence (AI) is widely applied in dementia research, including machine learning and deep learning methods for dementia diagnosis and progression detection. Computerized apps are also convenient tools for patients and caregivers to monitor cognitive function changes. Furthermore, social robots can potentially provide daily life support or guidance for the elderly who live alone. This review aims to provide an overview of AI applications in dementia research. We divided the applications into three categories according to different stages of cognitive impairment: (1) cognitive screening and training, (2) diagnosis and prognosis for dementia, and (3) dementia care and interventions. There are numerous studies on AI applications for dementia research. However, one challenge that remains is comparing the effectiveness of different AI methods in real clinical settings.

人工智能在痴呆症研究中的应用
全世界有 5000 多万老年人患有痴呆症,预计到 2050 年,这一数字将增至 1.5 亿。在我们等待有效治疗痴呆症的过程中,护理人员的负担和对医疗保健系统的经济影响预计会越来越大。研究人员正在不断探索早期检测痴呆症的新疗法和筛查方法。人工智能(AI)被广泛应用于痴呆症研究,包括用于痴呆症诊断和进展检测的机器学习和深度学习方法。计算机应用程序也是患者和护理人员监测认知功能变化的便捷工具。此外,社交机器人有可能为独居老人提供日常生活支持或指导。本综述旨在概述人工智能在痴呆症研究中的应用。我们根据认知障碍的不同阶段将应用分为三类:(1) 认知筛查和训练,(2) 痴呆症的诊断和预后,以及 (3) 痴呆症护理和干预。关于人工智能在痴呆症研究中的应用的研究不胜枚举。然而,比较不同人工智能方法在实际临床环境中的有效性仍是一项挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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