AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders
IntroductionEvaluating 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 ass...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1516065/full |
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| author | Diego D. Díaz-Guerra Marena de la C. Hernández-Lugo Yunier Broche-Pérez Carlos Ramos-Galarza Ernesto Iglesias-Serrano Zoylen Fernández-Fleites |
| author_facet | Diego D. Díaz-Guerra Marena de la C. Hernández-Lugo Yunier Broche-Pérez Carlos Ramos-Galarza Ernesto Iglesias-Serrano Zoylen Fernández-Fleites |
| author_sort | Diego D. Díaz-Guerra |
| collection | DOAJ |
| description | IntroductionEvaluating 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.ObjectivesThis 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.MethodologyThe 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.Anticipated resultsThe 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.ConclusionsBy 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. |
| format | Article |
| id | doaj-art-0018825b9dc14803b2b9129bd603a2c8 |
| institution | Kabale University |
| issn | 1664-0640 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-0018825b9dc14803b2b9129bd603a2c82025-01-13T06:10:17ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402025-01-011510.3389/fpsyt.2024.15160651516065AI-assisted neurocognitive assessment protocol for older adults with psychiatric disordersDiego D. Díaz-Guerra0Marena de la C. Hernández-Lugo1Yunier Broche-Pérez2Carlos Ramos-Galarza3Ernesto Iglesias-Serrano4Zoylen Fernández-Fleites5Department of Psychology, Faculty of Social Sciences, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Villa Clara, CubaDepartment of Psychology, Faculty of Social Sciences, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Villa Clara, CubaApplied Behavior Analysis Department, Prisma Behavioral Center, Miami, FL, United StatesCentro de Investigación en Mecatrónica y Sistemas Interactivos - MIST, Facultad de Psicología, Universidad Tecnológica Indoamérica, Quito, Ecuador”Dr. C. Luis San Juan Pérez” Provincial Teaching Psychiatric Hospital, Santa Clara, Villa Clara, CubaDepartment of Psychology, Faculty of Social Sciences, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Villa Clara, CubaIntroductionEvaluating 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.ObjectivesThis 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.MethodologyThe 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.Anticipated resultsThe 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.ConclusionsBy 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.https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1516065/fullneurocognitive assessmentsneuropsychologyolder adultsartificial intelligencecognitive disorders |
| spellingShingle | Diego D. Díaz-Guerra Marena de la C. Hernández-Lugo Yunier Broche-Pérez Carlos Ramos-Galarza Ernesto Iglesias-Serrano Zoylen Fernández-Fleites AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders Frontiers in Psychiatry neurocognitive assessments neuropsychology older adults artificial intelligence cognitive disorders |
| title | AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders |
| title_full | AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders |
| title_fullStr | AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders |
| title_full_unstemmed | AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders |
| title_short | AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders |
| title_sort | ai assisted neurocognitive assessment protocol for older adults with psychiatric disorders |
| topic | neurocognitive assessments neuropsychology older adults artificial intelligence cognitive disorders |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1516065/full |
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