Journal of Shanghai Jiao Tong University (Medical Science) ›› 2024, Vol. 44 ›› Issue (3): 393-398.doi: 10.3969/j.issn.1674-8115.2024.03.013

• Review • Previous Articles    

Progress in diagnosis and treatment of strabismus based on artificial intelligence technology

GUO Yonglin1,2(), CHEN Moxin1,2(), LIU Zheyuan3, LI Yifei1,2, WANG Ziqi1,2, SHU Qin1,2, LI Lin1,2()   

  1. 1.Department of Ophthalmology, Shanghai Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200011, China
    2.Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai 200011, China
    3.School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2023-10-18 Accepted:2023-01-26 Online:2024-03-28 Published:2024-04-29
  • Contact: LI Lin E-mail:guoyonglin@sjtu.edu.cn;evechen802@outlook.com;jannetlee1300@163.com
  • Supported by:
    Shanghai Science and Technology Innovation Action Plan Biomedical Technology Support Special Project(23S31900500);Target Commission of China Hospital Development Institute, Shanghai Jiao Tong University(CHDI-2022-DX-02);The Innovative Research Team of High-level Local Universities in Shanghai(SSMU-ZDCX20180401);Undergraduate Training Program on Innovation, Shanghai Jiao Tong University School of Medicine(1824026)

Abstract:

Strabismus, misalignment of the eyes arising from central nervous system dysregulation and extraocular muscles imbalance, commonly manifests in childhood, leading to amblyopia, binocular vision dysfunction, torticollis and other developmental and psychological disorders. This exerts a negative impact on individuals, families and society. Timely diagnosis and intervention are crucial to prevent permanent damage to vision and stereopsis. Presently, strabismus diagnosis is reliant on the ophthalmologists′ evaluations which results in a lack of efficiency and coverage. However, routine school screening proves inadequate in assessing strabismus degree with low accuracy. Therefore, how to improve the efficiency of strabismus screening is an issue of great importance. This paper delves into the present landscape of strabismus diagnosis and treatment, considering both local and global research advancements. It focuses on the evolution of artificial intelligence technology, illuminating the utilization of artificial intelligence models and algorithms in strabismus. By pinpointing and exploring their strengths and limitations, it offers valuable insights, paving the way for future investigations into artificial intelligence-assisted strabismus diagnosis and treatment.

Key words: strabismus, artificial intelligence, diagnosis, treatment, algorithm

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