Remote assessment of Parkinson’s disease symptom severity based on group interaction feature assistance-Reference-Cited by-同舟云学术

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Remote assessment of Parkinson’s disease symptom severity based on group interaction feature assistance

Published:2023-12-21 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Xue Zaifa,Lu Huibin,Zhang Tao^ORCID,Guo Xiaonan,Gao Le

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Postgraduate Innovation Fund Project of Hebei Province

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-02050-x.pdf

Reference50 articles.

1. Braga D, Madureira AM, Coelho L, Ajith R (2019) Automatic detection of Parkinson’s disease based on acoustic analysis of speech. Eng Appl Artif Intell 77:148–158

2. Zhang T, Lin LQ, Tian J, Xue ZF, Guo XN (2023) Voice feature description of Parkinson’s disease based on co-occurrence direction attribute topology. Eng Appl Artif Intell 122:106097

3. Omberg L, Neto EC, Perumal TM, Pratap A, Tediarjo A, Adams J, Bloem BR, Bot BM, Elson M, Goldman SM, Kellen MR, Kieburtz K, Klein A, Little MA, Schneider R, Suver C, Tarolli C, Tanner CM, Trister AD, Wilbanks J, Dorsey ER, Mangravite LM (2022) Remote smartphone monitoring of Parkinson’s disease and individual response to therapy. Nat Biotechnol 40(4):480–487

4. Zhang T, Lin LQ, Xue ZF (2023) A voice feature extraction method based on fractional attribute topology for Parkinson’s disease detection. Expert Syst Appl 219:119650

5. Moro-Velazquez L, Gomez-Garcia JA, Arias-Londoño JD, Dehak N, Godino-Llorente JI (2021) Advances in Parkinson’s Disease detection and assessment using voice and speech: a review of the articulatory and phonatory aspects. Biomed Signal Process Control 66:102418

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