Paper
2 May 2024 RehabGPT: a MaaS-based solution to large model building for digital rehabilitation
Hongsheng Wang, Zhangnan Zhong, Linwei Dai, Fei Wu, Xiao Ma, Junxiao Xue, Smirnov Pavel, Phuminh Lam, Qing Zhang, Feng Lin
Author Affiliations +
Proceedings Volume 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024; 131642U (2024) https://doi.org/10.1117/12.3019532
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2024, 2024, Langkawi, Malaysia
Abstract
Digital rehabilitation plays a crucial role in the treatment of chronic diseases, as it enables the assessment of disease grades and the recommendation of treatment measures. In this paper, we propose a generative pre-trained transformer towards rehabilitation (RehabGPT) via a model-as-a-service (MaaS) solution to facilitate foundation model building for digital rehabilitation on Alibaba's ModelScope platform. It offers scalable computational resources needed for pre-trained large models. It also provides tools for multi-modal feature extraction, 3D human mesh reconstruction and analysis of video sequences. RehabGPT automates various aspects of the model development workflow, such as hyper-parameter tuning and architecture selection, making it easier to achieve the desired results in rehabilitation tasks.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hongsheng Wang, Zhangnan Zhong, Linwei Dai, Fei Wu, Xiao Ma, Junxiao Xue, Smirnov Pavel, Phuminh Lam, Qing Zhang, and Feng Lin "RehabGPT: a MaaS-based solution to large model building for digital rehabilitation", Proc. SPIE 13164, International Workshop on Advanced Imaging Technology (IWAIT) 2024, 131642U (2 May 2024); https://doi.org/10.1117/12.3019532
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KEYWORDS
3D modeling

Video

Motion models

Data modeling

Education and training

Process modeling

Video coding

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