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深度学习在精神分裂诊断中的应用研究进展
Application of deep learning to the diagnosis of schizophrenia: a research progress

广西医学 页码:217-223

作者机构:曾啸,博士,讲师,研究方向为医学图像处理、生理信号智能分析。

基金信息:陕西省自然科学基础研究计划项目(2022JQ-649)

DOI:10.11675/j.issn.0253⁃4304.2024.02.07

  • 中文简介
  • 英文简介
  • 参考文献

精神分裂症是一种严重的精神疾病,其临床表现复杂多样。目前临床上诊断精神分裂症主要依靠病史询问、访谈、量表评估等,易发生漏诊和误诊。因此,许多研究者尝试采用深度学习方法辅助诊断精神分裂症。本文对精神分裂症自动诊断采用的数据类型和深度学习模型进行总结,并对该领域存在的挑战和未来的发展趋势进行分析和展望。

Schizophrenia is a serious mental illness, and its clinical manifestations are complex and varied. At present, the clinical diagnosis of schizophrenia mainly relies on history inquiry, interview, and scale evaluation, etc., which is prone to missed diagnosis and misdiagnosis. Therefore, many researchers have attempted to use deep learning method for the adjuvant diagnosis of schizophrenia. In this paper, the data types and deep learning model used in the automatic diagnosis of schizophrenia are summarized, and presence of challenges and future development trends in this field are analyzed and prospected. 

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