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Role-based questionnaire integration for Alzheimer’s disease monitoring in a user-centered digital platform.

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Názov: Role-based questionnaire integration for Alzheimer’s disease monitoring in a user-centered digital platform.
Alternate Title: Integrarea chestionarelor bazată pe roluri pentru monitorizarea bolii Alzheimer într-o platformă digitală centrată pe utilizator. (Romanian)
Autori: PETEAN, Corina-Elena, SĂNDULESCU, Virginia, BĂJENARU, Lidia, TEODORESCU, Paul, ȚÎRLEA, Cristian
Zdroj: Romanian Journal of Information Technology & Automatic Control / Revista Română de Informatică și Automatică; 2025, Vol. 35 Issue 4, p107-122, 16p
Predmety: ALZHEIMER'S disease, DIGITAL health, SUPERVISION, PATIENT monitoring, USER-centered system design, DIAGNOSIS
Abstract (English): Alzheimer’s disease (AD) requires early detection and continuous monitoring to enable effective management. Digital health platforms increasingly support this need, yet many lack usability, personalization, or integration across patient, caregiver, and clinician roles. This paper presents the NeuroPredict platform, a modular, role-based digital architecture which includes validated clinical assessment tools specific to AD. In compliance with the user-centered design (UCD) principles, the system provides automated scoring, longitudinal monitoring, and improved usability by adapting access and interaction to the requirements of the patients, caregivers, and clinicians. Internal assessments examined the reliability of differentiated workflows, scoring the algorithm accuracy, and platform stability. When compared to the current approaches that digitize instruments independently, the NeuroPredict platform shows how a role-based approach may enhance interpretability, ensure continuity of care, and facilitate integration into clinical workflows. These findings establish a solid technical basis for digital ecosystems in Alzheimer's disease monitoring which are clinically relevant, extensible, and interoperable, even though the validation with patient cohorts remains a future step. [ABSTRACT FROM AUTHOR]
Abstract (Romanian): Managementul eficient al bolii Alzheimer (AD) depinde de depistarea precoce și de monitorizarea susținută. Deși platformele de sănătate digitală (e-health) abordează această necesitate, multe prezintă deficiențe în personalizarea experienței de utilizare și în integrarea relației complexe pacient–îngrijitor– clinician. Această lucrare introduce NeuroPredict, o platformă digitală cu arhitectură modulară, proiectată conform principiilor Designului Centrat pe Utilizator (UCD). Platforma integrează chestionare clinice validate specifice afecțiunii AD, oferind funcționalități precum calculul automat al scorurilor și monitorizarea longitudinală. Sistemul optimizează fluxurile de lucru bazate pe roluri, adaptând interacțiunea și accesul la datele clinice pentru fiecare tip de utilizator (pacienți, îngrijitori și medici). Testele inițiale au confirmat fiabilitatea fluxurilor de lucru, precizia calculelor și stabilitatea generală a sistemului. Spre deosebire de demersurile axate pe simpla digitalizare a instrumentelor individuale, NeuroPredict demonstrează modul în care o abordare bazată pe roluri poate îmbunătăți semnificativ interpretabilitatea datelor și continuitatea îngrijirii, facilitând, în același timp, integrarea în ecosistemele clinice. Deși validarea clinică extinsă rămâne un pas viitor, rezultatele obținute stabilesc o bază tehnică solidă pentru dezvoltarea platformelor integrate, scalabile și interoperabile, destinate monitorizării AD. [ABSTRACT FROM AUTHOR]
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Databáza: Complementary Index
Popis
Abstrakt:Alzheimer’s disease (AD) requires early detection and continuous monitoring to enable effective management. Digital health platforms increasingly support this need, yet many lack usability, personalization, or integration across patient, caregiver, and clinician roles. This paper presents the NeuroPredict platform, a modular, role-based digital architecture which includes validated clinical assessment tools specific to AD. In compliance with the user-centered design (UCD) principles, the system provides automated scoring, longitudinal monitoring, and improved usability by adapting access and interaction to the requirements of the patients, caregivers, and clinicians. Internal assessments examined the reliability of differentiated workflows, scoring the algorithm accuracy, and platform stability. When compared to the current approaches that digitize instruments independently, the NeuroPredict platform shows how a role-based approach may enhance interpretability, ensure continuity of care, and facilitate integration into clinical workflows. These findings establish a solid technical basis for digital ecosystems in Alzheimer's disease monitoring which are clinically relevant, extensible, and interoperable, even though the validation with patient cohorts remains a future step. [ABSTRACT FROM AUTHOR]
ISSN:12201758
DOI:10.33436/v35i4y202508