Díaz-Guerra Diego D, Hernández-Lugo Marena de la C, Broche-Pérez Yunier, Ramos-Galarza Carlos, Iglesias-Serrano Ernesto, Fernández-Fleites Zoylen
Department of Psychology, Faculty of Social Sciences, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara, Cuba.
Applied Behavior Analysis Department, Prisma Behavioral Center, Miami, FL, United States.
Front Psychiatry. 2025 Jan 13;15:1516065. doi: 10.3389/fpsyt.2024.1516065. eCollection 2024.
Evaluating neurocognitive functions and diagnosing psychiatric disorders in older adults is challenging due to the complexity of symptoms and individual differences. An innovative approach that combines the accuracy of artificial intelligence (AI) with the depth of neuropsychological assessments is needed.
This paper presents a novel protocol for AI-assisted neurocognitive assessment aimed at addressing the cognitive, emotional, and functional dimensions of older adults with psychiatric disorders. It also explores potential compensatory mechanisms.
The proposed protocol incorporates a comprehensive, personalized approach to neurocognitive evaluation. It integrates a series of standardized and validated psychometric tests with individualized interpretation tailored to the patient's specific conditions. The protocol utilizes AI to enhance diagnostic accuracy by analyzing data from these tests and supplementing observations made by researchers.
The AI-assisted protocol offers several advantages, including a thorough and customized evaluation of neurocognitive functions. It employs machine learning algorithms to analyze test results, generating an individualized neurocognitive profile that highlights patterns and trends useful for clinical decision-making. The integration of AI allows for a deeper understanding of the patient's cognitive and emotional state, as well as potential compensatory strategies.
By integrating AI with neuro-psychological evaluation, this protocol aims to significantly improve the quality of neurocognitive assessments. It provides a more precise and individualized analysis, which has the potential to enhance clinical decision-making and overall patient care for older adults with psychiatric disorders.
由于症状的复杂性和个体差异,评估老年人的神经认知功能和诊断精神疾病具有挑战性。需要一种将人工智能(AI)的准确性与神经心理学评估的深度相结合的创新方法。
本文提出了一种用于人工智能辅助神经认知评估的新方案,旨在解决患有精神疾病的老年人的认知、情感和功能维度问题。它还探讨了潜在的代偿机制。
所提出的方案采用了全面、个性化的神经认知评估方法。它将一系列标准化和经过验证的心理测量测试与根据患者具体情况进行的个性化解读相结合。该方案利用人工智能通过分析这些测试的数据并补充研究人员的观察结果来提高诊断准确性。
人工智能辅助方案具有多个优点,包括对神经认知功能进行全面且定制化的评估。它采用机器学习算法来分析测试结果,生成个性化的神经认知概况,突出对临床决策有用的模式和趋势。人工智能的整合有助于更深入地了解患者的认知和情感状态以及潜在的代偿策略。
通过将人工智能与神经心理学评估相结合,该方案旨在显著提高神经认知评估的质量。它提供了更精确和个性化的分析,有可能加强对患有精神疾病的老年人的临床决策和整体患者护理。