Using Clinical Decision Intelligence Applications to Improve Pathways For Earlier Detection Of Underrecognized Cognitive Disorders.

JAR life Pub Date : 2023-01-01 DOI:10.14283/jarlife.2023.3
A S Khachaturian, B Cassin, G R Finney
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Abstract

Cost estimates for care for those with dementia and other cognitive impairments are rising globally, estimated to reach US $1 trillion by 2025. Lack of specialized personnel, infrastructure, diagnostic capabilities, and healthcare access impedes the timely identification of patients progressing to dementia, particularly in underserved populations. International healthcare infrastructure may be unable to handle existing cases in addition to a sudden increase due to undiagnosed cognitive impairment and dementia. Healthcare bioinformatics offers a potential route for quicker access to healthcare services; however, a better preparedness plan must be implemented now if expected demands are to be met. The most critical consideration for implementing artificial intelligence/machine learning (AI/ML) -driven clinical decision intelligence applications (CDIA) is ensuring patients and practitioners take action on the information provided.

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使用临床决策智能应用程序改善早期发现未被认识的认知障碍的途径。
在全球范围内,对痴呆症和其他认知障碍患者的护理费用估计正在上升,到2025年估计将达到1万亿美元。缺乏专业人员、基础设施、诊断能力和医疗保健服务阻碍了及时发现进展为痴呆症的患者,特别是在服务不足的人群中。国际卫生保健基础设施可能无法处理现有病例,而且由于未确诊的认知障碍和痴呆症而突然增加。医疗保健生物信息学为更快获得医疗保健服务提供了一条潜在途径;但是,如果要满足预期的需求,现在就必须实施更好的准备计划。实施人工智能/机器学习(AI/ML)驱动的临床决策智能应用(CDIA)的最关键考虑因素是确保患者和从业人员根据所提供的信息采取行动。
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