ARIAL@IJCAI 2025 : 8th Workshop on AI for Aging, Rehabilitation, and Intelligent Assisted Living (ARIAL) @IJCAI'25
The 8th edition of ARIAL@IJCAI25 will be held on August 16 - 22, 2025, in Montreal, Canada. In this workshop, we invite previously unpublished and novel submissions in the following areas (pertaining to aging and rehabilitation), but not limited to:
- Methods and protocols for multimodal data collection, data annotation, and data labeling with older adult populations.
- Data cleaning, curation, sharing, and harmonization.
- Data analytics and visualization techniques for older adults healthcare data.
- Methodologies for big data and large-scale machine learning, including cloud computing.
- Methods for overcoming challenges in machine learning, such as managing incomplete, imbalanced, miss-labeled and noisy datasets.
- Techniques for virtual rehabilitation, virtual coaches, and telemedicine.
- Development and deployment of long-term sensor-based remote monitoring systems.
- Audio/video, multimodal interaction for patient engagement, exercise monitoring, successful delivery of rehabilitation.
- Addressing privacy concerns of patient data, e.g., privacy-protecting sensing modalities, federated learning, and differential privacy.
- Machine learning and deep learning algorithms to identify anomalous, harmful, life-threatening, and abnormal behaviors in older care settings.
- Machine learning approaches for analyzing electronic health record and administrative data.
- AI approaches for continuous streaming, monitoring, and analysis of health, activity, contextual, and online data for older adults.
- Techniques for handling data biases, and other biases related to sex, gender, ethnicity, and age (e.g., fair machine learning strategies).
- Machine learning methods for measuring health indicators, and progression of physical and cognitive health, e.g., frailty, dementia, mental health, and gait stability.
- AI approaches for data fusion from multi-modal sensor interaction and ensemble algorithm development (e.g., multi-view learning approaches) for comprehensive care.
- Advanced deep learning techniques for medical informatics, aging and rehabilitation.
- Application of LLMs and Generative AI in geriatric healthcare and biomedical data processing.
- NLP for enhancing communication and monitoring in elderly care.
The paper should be submitted to the ARIAL Workshop using EasyChair link (https://easychair.org/conferences/?conf=arialijcai2025) in the LNCS/CCIS one-column page format. We will accept long papers (12-15 pages) and short papers (not less than 6 pages).
All the accepted papers will be published in the Springer's Communications in Computer and Information Science (CCIS) proceedings volume.
For further details, please reach out to [email protected] / [email protected].
- Methods and protocols for multimodal data collection, data annotation, and data labeling with older adult populations.
- Data cleaning, curation, sharing, and harmonization.
- Data analytics and visualization techniques for older adults healthcare data.
- Methodologies for big data and large-scale machine learning, including cloud computing.
- Methods for overcoming challenges in machine learning, such as managing incomplete, imbalanced, miss-labeled and noisy datasets.
- Techniques for virtual rehabilitation, virtual coaches, and telemedicine.
- Development and deployment of long-term sensor-based remote monitoring systems.
- Audio/video, multimodal interaction for patient engagement, exercise monitoring, successful delivery of rehabilitation.
- Addressing privacy concerns of patient data, e.g., privacy-protecting sensing modalities, federated learning, and differential privacy.
- Machine learning and deep learning algorithms to identify anomalous, harmful, life-threatening, and abnormal behaviors in older care settings.
- Machine learning approaches for analyzing electronic health record and administrative data.
- AI approaches for continuous streaming, monitoring, and analysis of health, activity, contextual, and online data for older adults.
- Techniques for handling data biases, and other biases related to sex, gender, ethnicity, and age (e.g., fair machine learning strategies).
- Machine learning methods for measuring health indicators, and progression of physical and cognitive health, e.g., frailty, dementia, mental health, and gait stability.
- AI approaches for data fusion from multi-modal sensor interaction and ensemble algorithm development (e.g., multi-view learning approaches) for comprehensive care.
- Advanced deep learning techniques for medical informatics, aging and rehabilitation.
- Application of LLMs and Generative AI in geriatric healthcare and biomedical data processing.
- NLP for enhancing communication and monitoring in elderly care.
The paper should be submitted to the ARIAL Workshop using EasyChair link (https://easychair.org/conferences/?conf=arialijcai2025) in the LNCS/CCIS one-column page format. We will accept long papers (12-15 pages) and short papers (not less than 6 pages).
All the accepted papers will be published in the Springer's Communications in Computer and Information Science (CCIS) proceedings volume.
For further details, please reach out to [email protected] / [email protected].