Application of deep learning algorithm in the recognition of cryptococcosis and talaromycosis skin lesions.

Journal: Mycoses
PMID: 37132426

Abstract

BACKGROUND: Cryptococcosis and talaromycosis are known as 'neglected epidemics' due to their high case fatality rates and low concern. Clinically, the skin lesions of the two fungal diseases are similar and easily misdiagnosed. Therefore, this study aims to develop an algorithm to identify cryptococcosis/talaromycosis skin lesions.

Authors

  • Wudi Wei
    Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning 530021, Guangxi, China.
  • Xiaotao He
    Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, China.
  • Xiuli Bao
    China (Guangxi)-ASEAN Joint Laboratory of Emerging Infectious Diseases, Guangxi Medical University, Nanning, Guangxi, PR China.
  • Gang Wang
    National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
  • Qiang Luo
    Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, PR China; Department of Psychology and the Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge CB2 3EB, UK; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, PR China. Electronic address: qluo@fudan.edu.cn.
  • Lixiang Chen
    China (Guangxi)-ASEAN Joint Laboratory of Emerging Infectious Diseases, Guangxi Medical University, Nanning, Guangxi, PR China.
  • Baili Zhan
    Guangxi-ASEAN Collaborative Innovation Center for Major Disease Prevention and Treatment, Life Sciences Institute, Guangxi Medical University, Nanning, China.
  • Jingzhen Lai
    Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning 530021, Guangxi, China.
  • Junjun Jiang
    Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning 530021, Guangxi, China.
  • Li Ye
    Guangxi Key Laboratory of AIDS Prevention and Treatment & Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, School of Public Health, Guangxi Medical University, Nanning 530021, Guangxi, China.
  • Hao Liang
    a Marine College Shandong University (weihai) , Shandong , China .

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