CLADSI: Deep Continual Learning for Alzheimer's Disease Stage Identification Using Accelerometer Data-Reference-Cited by-同舟云学术

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CLADSI: Deep Continual Learning for Alzheimer's Disease Stage Identification Using Accelerometer Data

Published:2024-06 Issue:6 Volume:28 Page:3401-3410
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Bringas Santos¹^ORCID,Duque Rafael²^ORCID,Lage Carmen³^ORCID,Montaña José Luis²^ORCID

Affiliation:

1. Department of Artificial Intelligence, Axpe Consulting Cantabria, Camargo, Spain

2. Faculty of Science, Department of Mathematics, Statistics and Computer Science, University of Cantabria, Santander, Spain

3. Global Brain Health Institute, University of California, San Francisco, CA, USA

Funder

University of Cantabria, Government of Cantabria and Banco Santander

Proyectos Puente 2021

Consejería de Universidades, Igualdad, Cultura y Deporte, Goverment of Cantabria

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221020/10550931/10506537.pdf?arnumber=10506537

Reference29 articles.

1. Drug therapies for chronic conditions and risk of Alzheimer's disease and related dementias: A scoping review

2. Clinical diagnosis of Alzheimer's disease: recommendations of the International Working Group

3. A longitudinal study of gait function and characteristics of gait disturbance in individuals with Alzheimer's disease

4. Continuous gait monitoring discriminates community‐dwelling mild Alzheimer's disease from cognitively normal controls

5. Gait and Balance Analysis for Patients With Alzheimer's Disease Using an Inertial-Sensor-Based Wearable Instrument

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1. Editorial AI Driven Internet of Medical Things for Smart Healthcare Applications: Challenges and Future Trends;IEEE Journal of Biomedical and Health Informatics;2024-06

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