Search

Your search keyword '"He, Baihui"' showing total 14 results
Start Over Author "He, Baihui"
14 results on '"He, Baihui"'

5. Evaluating children with vestibular migraine through vestibular test battery: A cross-sectional investigation

Author

Zhang, Fan, primary, Shen, Jiali, additional, Zhu, Qi, additional, Wang, Lu, additional, Ma, Xiaobao, additional, He, Baihui, additional, Yang, Yang, additional, Wang, Wei, additional, Chen, Xiangping, additional, Zhang, Qing, additional, Jin, Yulian, additional, Duan, Maoli, additional, Chen, Jianyong, additional, and Yang, Jun, additional

Published
2022
Full Text
View/download PDF

7. Pseudo-Temporal Analysis of Single-Cell RNA Sequencing Reveals Trans-Differentiation Potential of Greater Epithelial Ridge Cells Into Hair Cells During Postnatal Development of Cochlea in Rats

Author

Chen, Jianyong, primary, Gao, Dekun, additional, Chen, Junmin, additional, Hou, Shule, additional, He, Baihui, additional, Li, Yue, additional, Li, Shuna, additional, Zhang, Fan, additional, Sun, Xiayu, additional, Jin, Yulian, additional, Sun, Lianhua, additional, and Yang, Jun, additional

Published
2022
Full Text
View/download PDF

9. Single-Cell RNA Sequencing Analysis Reveals Greater Epithelial Ridge Cells Degeneration During Postnatal Development of Cochlea in Rats

Author

Chen, Jianyong, primary, Gao, Dekun, additional, Chen, Junmin, additional, Hou, Shule, additional, He, Baihui, additional, Li, Yue, additional, Li, Shuna, additional, Zhang, Fan, additional, Sun, Xiayu, additional, Mammano, Fabio, additional, Sun, Lianhua, additional, Yang, Jun, additional, and Zheng, Guiliang, additional

Published
2021
Full Text
View/download PDF

12. The Correlation of a 2D Volume-Referencing Endolymphatic-Hydrops Grading System With Extra-Tympanic Electrocochleography in Patients With Definite Ménière's Disease

Author

He, Baihui, primary, Zhang, Fan, additional, Zheng, Hui, additional, Sun, Xiayu, additional, Chen, Junmin, additional, Chen, Jianyong, additional, Liu, Yupeng, additional, Wang, Lu, additional, Wang, Wei, additional, Li, Shuna, additional, Yang, Jun, additional, and Duan, Maoli, additional

Published
2021
Full Text
View/download PDF

13. Distinct Expression Patterns of Apoptosis and Autophagy-Associated Proteins and Genes during Postnatal Development of Spiral Ganglion Neurons in Rat

Author

Hou, Shule, primary, Chen, Penghui, additional, Chen, Jiarui, additional, Chen, Junmin, additional, Sun, Lianhua, additional, Chen, Jianyong, additional, He, Baihui, additional, Li, Yue, additional, Qin, Huan, additional, Hong, Yuren, additional, Li, Shuna, additional, He, Jingchun, additional, Gao, Dekun, additional, Mammano, Fabio, additional, and Yang, Jun, additional

Published
2020
Full Text
View/download PDF

14. [Characteristics of wideband tympanometry in patients with Ménière's disease based on neutral network].

Author

Wu Y, He B, Shen M, Yang Y, Jin Y, Zhang Q, Yang J, and Li S

Subjects
Acoustic Impedance Tests, Adult, Gadolinium DTPA, Humans, Magnetic Resonance Imaging, Ear, Inner, Endolymphatic Hydrops, Meniere Disease
Abstract

Objective: To construct a prediction model for Ménière's disease based on neural network and evaluate its prediction ability. Methods: Sixty-four patients with Ménière's disease underwent gadolinium enhanced magnetic resonance imaging of inner ear which showed endolymphatic hydrops. Meanwhile, 40 healthy adults were enrolled as controls. The database of wideband tympanometry of patients and control subjects was analyzed, and the neural network model was established by MATLAB 2021a software. The prediction ability of the model was evaluated by accuracy, positive predictive value, negative predictive value, the Youden index, sensitivity, specificity, receiver operating characteristic curve and area under curve （AUC）. Results: A feedforward network model was built with a single hidden layer to predict Ménière's disease with wideband tympanometry. There were 104 features in the input layer, 13 neuron nodes in the hidden layer and 1 output neuron in the output layer. The accuracy of the model was 83.2%, the positive predictive value was 80.7%, the negative predictive value was 84.3%, the sensitivity was 76.5%, the specificity was 83.7%, the Youden index was 0.602, and the AUC was 0.855. Conclusion: Based on neural network, the prediction model of Ménière's disease with high accuracy was constructed according to the results of wideband tympanometry, which provided reference for the diagnose of Ménière's disease., Competing Interests: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose., (Copyright© by the Editorial Department of Journal of Clinical Otorhinolaryngology Head and Neck Surgery.)

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results