Multimodal deep learning-based diagnostic model for BPPV.

Journal: BMC medical informatics and decision making
Published Date: Mar 21, 2024

Abstract

BACKGROUND: Benign paroxysmal positional vertigo (BPPV) is a prevalent form of vertigo that necessitates a skilled physician to diagnose by observing the nystagmus and vertigo resulting from specific changes in the patient's position. In this study, we aim to explore the integration of eye movement video and position information for BPPV diagnosis and apply artificial intelligence (AI) methods to improve the accuracy of BPPV diagnosis.

Authors

  • Hang Lu
  • Yuxing Mao
    State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing University, Chongqing, China. myx@cqu.edu.cn.
  • Jinsen Li
    Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA.
  • Lin Zhu
    Institute of Environmental Technology, College of Environmental and Resource Sciences; Zhejiang University, Hangzhou 310058, China.

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