Automatic Judgement, Cataract, Diagnoses Disease, High Myopia, Myopia, Risk Reduction
Conditions
Keywords
highly myopic cataract, artificial intelligence, cataract, big data
Brief summary
This study aims to establish a multi-center artificial intelligence model for the accurate calculation of intraocular lens and its clinical application in highly myopic cataract, so as to improve the accuracy of the prediction of postoperative diopter in highly myopic cataract patients.
Detailed description
High myopia cataract (HMC) is a complex cataract with high risk of blindness. At present, there are nearly 300 million people with high myopia in the world, which will increase to 500 million by 2020. Asia is the high incidence of myopia in the world. At present, there are more than 500 million people with myopia in China alone, of which nearly 100 million are high myopia, and this number is still growing rapidly. Correspondingly, the incidence rate of cataract with high myopia has also increased rapidly, which accounts for over 40% of cataract surgery. In the early stage of the project team's analysis of refractive error after high myopia cataract surgery, it was found that the accuracy of intraocular lens calculation formula, which is widely recommended for high myopia cataract at present, is still worrying, because most of these formulas are based on the European and American eye data, while the European and American databases have few ultra high myopia data, which greatly affects the formula's accuracy In addition, the calculation of the existing formula needs to include multiple biometric indicators, and can be obtained based on complex algorithms. Artificial intelligence technology is exactly an effective means to solve this kind of problem. Therefore, based on the data of Asian population with high myopia and high incidence, the establishment of an intelligent model for the accurate calculation of high myopia cataract IOL will greatly improve the measurement accuracy Sex. Therefore, the purpose of this study is to establish a multi-center artificial intelligence model for the accurate calculation of intraocular lens and its clinical application in highly myopic cataract, so as to improve the accuracy of the prediction of postoperative diopter in highly myopic cataract patients.
Interventions
DEVICEnewly-invented AI model
Apply newly-invented AI models to assist in determining surgical plans and outcome prediction.
Sponsors
Shanghai High Myopia Study Group
Eye and ENT Hospital of Fudan University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Inclusion criteria
Axial length ≥ 26 mm and patients with high myopia complicated by cataracts who visit our hospital. Preoperative anterior segment photography and cataract severity assessment, along with fundus OCT examination, have been performed. If surgical treatment is conducted, the postoperative follow-up period should be no less than 1 month. There are no missing clinical data before and after the surgery.
Exclusion criteria
Patients who are unable to cooperate with the required examinations for this study.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| a multi-center artificial intelligence model for the accurate calculation of intraocular lens and its clinical application in highly myopic cataract | 10 YEARS |
| a multi-center artificial intelligence model for the cataract grading and its clinical application in highly myopic cataract | 8 years |
Secondary
| Measure | Time frame |
|---|---|
| a multi-center artificial intelligence model for the risk prediction of perioperative complications and its clinical application in highly myopic cataract | 10 years |
| a multi-center artificial intelligence model for the surgical outcome prediction and its clinical application in highly myopic cataract | 10 years |
Countries
China
Contacts
CONTACTWENWEN HE
CONTACTKEKE ZHANG
STUDY_CHAIRXIANGJIA ZHU
Eye & ENT Hospital of Fudan University
Outcome results
None listed