Corneal biomechanics in early diagnosis of keratoconus using artificial intelligence

被引:1
|
作者
Huo, Yan [1 ]
Chen, Xuan [1 ]
Khan, Gauhar Ali [2 ]
Wang, Yan [1 ,2 ,3 ,4 ]
机构
[1] Nankai Univ, Sch Med, Tianjin, Peoples R China
[2] Tianjin Med Univ, Clin Coll Ophthalmol, Tianjin, Peoples R China
[3] Nankai Univ, Affiliated Eye Hosp, Tianjin Key Lab Ophthalmol & Visual Sci, Tianjin Eye Inst,Tianjin Eye Hosp, 4 Gansu Rd, Tianjin 300020, Peoples R China
[4] Nankai Univ, Nankai Eye Inst, Tianjin, Peoples R China
关键词
Corneal biomechanics; Artificial intelligence; Machine learning; Keratoconus; Early keratoconus; SUBCLINICAL KERATOCONUS; MANIFEST KERATOCONUS; TOMOGRAPHY; NONCONTACT; PARAMETERS; HEALTHY; SUSPECT; TONOMETRY; ECTASIA; ABILITY;
D O I
10.1007/s00417-023-06307-7
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
Keratoconus is a blinding eye disease that affects activities of daily living; therefore, early diagnosis is crucial. Great efforts have been made toward an early diagnosis of keratoconus. Recent studies have shown that corneal biomechanics is associated with the occurrence and progression of keratoconus. Hence, detecting changes in corneal biomechanics may provide a novel strategy for early diagnosis. However, an early keratoconus diagnosis remains challenging due to the subtle and localized nature of its lesions. Artificial intelligence has been used to help address this problem. Herein, we reviewed the literature regarding three aspects of keratoconus (keratoconus, early keratoconus, and keratoconus grading) based on corneal biomechanical properties using artificial intelligence. Furthermore, we summarized the current research progress, limitations, and possible prospects.
引用
收藏
页码:1337 / 1349
页数:13
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