Automated methods for diagnosis of Parkinson’s disease and predicting severity level
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-06626-y.pdf
Reference210 articles.
1. Agarwal A, Chandrayan S, Sahu SS (2016) Prediction of Parkinson’s disease using speech signal with extreme learning machine. In: 2016 international conference on electrical, electronics, and optimization techniques (ICEEOT). IEEE, pp 3776–3779
2. Ahlrichs C, Lawo M (2013) Parkinson’s disease motor symptoms in machine learning: a review. arXiv preprint arXiv:1312.3825
3. Aich S, Kim HC, Hui KL, Al-Absi AA, Sain M et al (2019) A supervised machine learning approach using different feature selection techniques on voice datasets for prediction of Parkinson’s disease. In: 2019 21st international conference on advanced communication technology (ICACT). IEEE, pp. 1116–1121
4. Akyol K (2017) A study on the diagnosis of Parkinson’s disease using digitized wacom graphics tablet dataset. Int J Inf Technol Comput Sci 9:45–51
5. Al-Fatlawi AH, Jabardi MH, Ling SH (2016) Efficient diagnosis system for Parkinson’s disease using deep belief network. In: 2016 IEEE congress on evolutionary computation (CEC). IEEE, pp 1324–1330
Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Parkinson’s Disease and Photobiomodulation: Potential for Treatment;Journal of Personalized Medicine;2024-01-19
2. Speech features-based Parkinson’s disease classification using combined SMOTE-ENN and binary machine learning;Health and Technology;2024-01-15
3. An Adaptive Intelligent Polar Bear (AIPB) Optimization-Quantized Contempo Neural Network (QCNN) model for Parkinson’s disease diagnosis using speech dataset;Biomedical Signal Processing and Control;2024-01
4. Clinically Informed Automated Assessment of Finger Tapping Videos in Parkinson’s Disease;Sensors;2023-11-13
5. A Survey of Machine Learning Methods for Diagnosing Parkinson's Disease with Handwriting;2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT);2023-10-26
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3