Modeling Parkinson’s Disease Aided Diagnosis with Multi-Instance Learning: An Effective Approach to Mitigate Label Noise-Reference-Cited by-同舟云学术

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Modeling Parkinson’s Disease Aided Diagnosis with Multi-Instance Learning: An Effective Approach to Mitigate Label Noise

Published:2023-12-17 Issue: Volume: Page:936-943
ISSN:
Container-title:2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS)
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Author:

Xu Zheyuan¹,Nan Fengtao¹,Qi Jun²,Yang Yun¹,Wang Xulong³,Yang Po³

Affiliation:

1. National Pilot School of Software Yunnan University,Kunming,China

2. Xi’an JiaoTong-Liverpool University,Department of Computing,Suzhou,China

3. University of Sheffield,Department of Computer Science,Sheffieid,UK

Funder

National Natural Science Foundation of China

Young Scientists Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10475889/10475881/10476144.pdf?arnumber=10476144

Reference30 articles.

1. Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results

2. Ellipse fitting model for improving the effectiveness of life‐logging physical activity measures in an Internet of Things environment

3. Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review

4. An overview of data fusion techniques for Internet of Things enabled physical activity recognition and measure

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