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The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Auxiliary diagnosis of heterogeneous data of Parkinson’s disease based on improved convolution neural network

Yin, Dai, Zhao, Yiqi, Wang, Yang, Zhao, Wenpu, Hu, Xiaoming·2020·Multimedia Tools and Applications

Overview

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Crossref · 10.1007/s11042-020-08984-6

Cites

6 of 6 references verified0 citation errors · 0 not checkable

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Citations

Cites

Show all 6 references

Research works printed but not linked: 13

  1. Alzubi J, Nayyar A, Kumar A (2018) Machine learning from theory to algorithms: an overview [C]//journal of physics: conference series. IOP Publishing 1142(1):012012
  2. Cheng Y, Huifang S (2017) Interpretation of 2016 Chinese PD diagnostic criteria [J]. Chinese Journal of Practical Internal Medicine 37(02):124–126
  3. Zhao Dan, Mao Chuan-Wan, Huang Jianhe 2010, et al. A magnetic resonance imaging study of the pars Compacta of Substantia Nigra in PD [J]. Chin J Clin Neurosci, 18(2):130–134.
  4. Fang Y, Gang Y, Jun X (2014) Meta analysis of risk factors and protective factors for Parkinson disease in Chinese population [J]. Clin Neurol 27(02):111–115
  5. Huang Haidong, Deng Jinglan, Huan Yi 2004, et al. The application of measurement of the width of pars Compacta of Substantia Nigra in differential diagnosis on Parkinson’ s disease and vascular parkinsonism on MRI [J]. Clin Neurol, 17(01):11–13.
  6. Li Jianchuan, Qin Guojun, Wen Xisen 2002, et al. Over-fitting in neural network learning algorithms and its solving strategies [J]. Journal of Vibration, Measurement & Diagnosis, 22(04):260–264.
  7. Feng Jieying, Huang Biao, Zhong Xiaoling 2013, et al. Imaging diagnosis of PD and Parkinson's superposition syndrome [J]. Radio Practice, 28(11):1105–1108.
  8. Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks [C]//Advances in neural information processing systems, pp 1097–1105
  9. Quanhua Z, Gao J, Li Y (2015) Multi-feature texture image segmentation based on tessellation technique [J]. Chin J Sci Instrum 36(11):2519–2530
  10. Wang F (2016) Research and Applications Based The Improved Convolutional Neural Network [D]. Nanjing University of Posts and Telecommunications, Nanjing
  11. Zhang Wen-qian, Su Hai-xia, Shang Lei 2017, et al. A comparative study on prediction of Alzheimer's disease progression based on BP and RBF neural network [J]. Progress in Modern Biomedicine, 17(04):738–741.
  12. Xu Dongfeng, Lei Yi, Xia Jun 2018, et al. Diagnosis and imaging findings of PD [J]. Hainan Med, 29(03):381–384.
  13. Yueqi Z, Wang G (2016) International movement disorders association new standard for clinical diagnosis of PD (2015)[J]. Diagn Concepts Pract 15(02):122–123

Cited by

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Metadata

Authors
Yin, D., Zhao, Y., Wang, Y., Zhao, W., & Hu, X.
Affiliations
  • The University of Sydney (AU)
  • Neusoft (China) (CN)
  • Northeastern University (CN)
Venue
Multimedia Tools and Applications
Published
2020-06-18
Volume
79
Issue
33-34
Pages
24199-24224
ISSN
  • 1380-7501 (ISSN-L)
  • 1573-7721
OpenAlex
W3036922081
Cited by
15
References
6
Citations by year
2026: 3 · 2025: 1 · 2024: 3 · 2023: 1 · 2022: 3 · 2021: 4
FWCI
0.87
Type
journal article
Language
en
Open access
closed
Licence
Locations
Multimedia Tools and Applications (publishedVersion)
Topics
  • Health Sciences › Medicine › Clinical Neurology › Parkinson's Disease Mechanisms and Treatments
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords
Parkinson's disease, computer-aided diagnosis, T2-weighted MRI, heterogeneous data fusion, clinical data, Gabor filters, improved convolutional neural network, ReLU activation, neurodegenerative diseases

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This page
CoChat. (2026). Citation check: Auxiliary diagnosis of heterogeneous data of Parkinson’s disease based on improved convolution neural network. https://app.cochat.ai/papers/10.1007/s11042-020-08984-6
The paper
Yin, D., Zhao, Y., Wang, Y., Zhao, W., & Hu, X. (2020). Auxiliary diagnosis of heterogeneous data of Parkinson’s disease based on improved convolution neural network. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-020-08984-6

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.