Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Agentic artificial intelligence in cognitive screening: A translational roadmap for dementia care
0
Zitationen
3
Autoren
2025
Jahr
Abstract
Conventional dementia screening tools, whether paper tests or static artificial intelligence (AI) models, capture only a snapshot of cognition and need to be adminstered periodically. Yet decline is dynamic, shaped by environment, comorbidities, and life history. Current approaches rarely adapt, integrate feedback, or provide transparent reasoning that clinicians can trust. We propose agentic AI systems: modular agents built on large language models (LLMs) that collaborate, adapt, and mirror interdisciplinary care. The Cognitive Agent Lab exemplifies this framework, emphasizing functional aspects (inputs, outputs, workflows) and non-functional aspects (transparency, adaptivity, robustness, clinical alignment). Embedding reasoning and collaboration, agentic AI offers a roadmap toward more personalized and explainable cognitive health tools.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.239 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.428 Zit.