IJCAI 2022

The 2nd AI for Cognitive and Physical Frailty Seminar (AIF)

9:00 AM - 12:30 PM, July 24, 2022 (GMT+2) | Gallerie 3-4, Messe Wien, Vienna, Austria
(i.e., 3:00 PM - 6:30 PM, July 24, 2022 (GMT+8) | Singapore & Beijing)


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About IJCAI

The International Joint Conference on Artificial Intelligence (IJCAI) is the leading conference in the field of Artificial Intelligence. It covers a broad range of research areas in the field of AI. The conference series has been organized by the nonprofit IJCAI Organization since 1969, making it the oldest premier AI conference series which gathers researchers of AI all around the world.

Introduction

Frailty refers to a multi-dimensional syndrome that may include physical, psychological, cognitive, and social impairments. Frailty is a consequence of the cumulative decline in many physiological systems, resulting in the depletion of homoeostatic reserves such that a minor stressor event can trigger disproportionate changes in health status. It may represent a transition phase between successful ageing and adverse health-related outcomes, including dependency, disability, hospitalization, and death. Hence, frailty is also a condition to target for restoring robustness in at-risk individuals. Early identification and effective intervention for cognitive and physical frailty can potentially reduce the incidence of adverse events, improve frail individuals' quality of life, and reduce healthcare and social costs. However, most existing frailty assessment and intervention programs are conducted in clinical settings, which is neither scalable nor sustainable. Their costs may also be unaffordable to a significant portion of the frail population.

Artificial Intelligence is a seismic force shaping the 21st century and has nurtured one of the largest computer science research communities. Interdisciplinary research and the application of AI technologies in the field of frailty offer potential solutions to improve efforts at the identification and intervention of frailty. AI technologies can help assess the potential risk of frailty and pre-frailty in home and community environments instead of relying on clinical settings alone. AI technologies can also be employed to produce customizable, adaptable, and personalized intervention plans, e.g., for physical exercise, nutrition, and polypharmacy management, to maximize intervention effectiveness.

This seminar aims to bring together researchers, medical practitioners, representatives of potential beneficiaries, relevant members of social groups, relevant industry stakeholders, and potential investors in the field of AI in cognitive and physical frailty, rehabilitation, healthcare, and ageing. We look forward to discussing how AI can assist frail people through early detection and personalized intervention, and how AI can improve the efficiency of the existing healthcare systems through better healthcare delivery and utilization of care resources. Researchers interested in or would like to contribute to AI for cognitive and physical frailty are welcome to attend the seminar.


Invited Talks

Prof. Andrew Sixsmith
Simon Fraser University, Canada
Prof. Huanhuan Chen
University of Science and Technology of China, China
Prof. Martin J. McKeown
The University of British Columbia, Canada

Schedule

Time (GMT+2) Speaker Title Record
9:00 AM - 9:05 AM Prof. Zhiqi Shen Opening Remarks
Invited Talk
9:05 AM - 9:40 AM Prof. Andrew Sixsmith Turning AgeTech Research into Real-world Products and Services: The AGE-WELL Approach
Research Paper Presentations
9:40 AM - 9:55 AM Dr. Di Wang Computerized Assessment of Frailty in Community Settings
9:55 AM - 10:10 AM Prof. Peng Han VGE: Gene-Disease Association by Variational Graph Embedding
Invited Talk
10:10 AM - 10:45 AM Prof. Martin J. McKeown The Promise of AI for Elder Healthcare: A Clinician’s Perspective
Coffee Break
10:45 AM - 11:15 AM - -
Research Paper Presentations
11:15 AM - 11:30 AM Dr. Xuejiao Zhao A Person–Environment Fit Model for Aging-in-Place
11:30 AM - 11:45 AM Dr. Hongfei Yang Frailty Identification Using Machine Learning Methodologies: A Systematic Review
11:45 AM - 12:00 PM Dr. Maryam Mirian Smartphone-based Automatic Motor Examination for Parkinson's Disease: A Machine Learning-based Explainable Platform for Diagnosis and Severity Evaluation
Invited Talk
12:00 PM - 12:35 PM Prof. Huanhuan Chen Big-data Knowledge Engineering and Its Applications
12:35 PM - 12:40 PM Dr. Di Wang Closing

Committee

Cuntai Guan
Nanyang Technological University, Singapore
Cyril Leung
The University of British Columbia, Canada
Jing Jih Chin
Tan Tock Seng Hospital, Singapore
Lizhen Cui
Shandong Unviersity, China
Takayuki Ito
Kyoto University, Japan
Yiqiang Chen
Chinese Academy of Sciences, China
Tao Wang
Peking University, China
Zhiqi Shen
Nanyang Technological University, Singapore
Chunyan Miao
Nanyang Technological University, Singapore
Hong Xu
Nanyang Technological University, Singapore
Zhiwei Zeng
Nanyang Technological University, Singapore
Xuejiao Zhao
Nanyang Technological University, Singapore

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