Optimization method for predicting refraction adjustment value in SMILE refractive surgery and system

A technology of refractive surgery and optimization method, which is applied in the optimization and system field of predicting diopter adjustment value in SMILE refractive surgery, to achieve the effect of improving accuracy and reducing prediction deviation

Active Publication Date: 2019-02-01
季书帆
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Problems solved by technology

However, there are still many problems to be optimized to further improve the accuracy of Nomogram value prediction in SMILE surgery

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  • Optimization method for predicting refraction adjustment value in SMILE refractive surgery and system
  • Optimization method for predicting refraction adjustment value in SMILE refractive surgery and system
  • Optimization method for predicting refraction adjustment value in SMILE refractive surgery and system

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Embodiment Construction

[0050] The technical content of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0051] In the currently available training surgery cases, the number of cases with different Nomogram (diopter adjustment value) values ​​is often different, which is usually determined by the actual distribution of cases. scarcity. However, the unbalanced distribution of training data usually causes the learning model to tend to fit cases of popular categories, resulting in low prediction accuracy for minority cases. Therefore, optimizing the distribution balance of the training data will help improve the existing prediction results. In addition, there is inevitably a certain deviation between the prediction results of the machine learning algorithm and the actual setting value of the doctor. Designing an optimization algorithm to reduce this deviation will help to maximize the fitting of the doctor's experience and...

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Abstract

The invention discloses an optimization method for predicting a refraction adjustment value in an SMILE refractive surgery and system. The method comprises the following steps: an optimal machine learning algorithm is used, the preoperative parameters of training samples and the post-operative refraction are used as training attributes, and a prediction model is trained and generated; as for a to-be-predicted new case, the post-operative refraction is used as a target attribute and set as an ideal value, and in cooperation with the preoperative parameters of the to-be-predicted new case, the prediction model is used to generate a Nomogram prediction value. The method can effectively improve the prediction accuracy of the Nomogram prediction value, dependence on experts in a preoperative plan making process can be reduced, the professional threshold for preoperative plan making is reduced, and the preoperative plan making accuracy is further enhanced.

Description

technical field [0001] The present invention relates to an optimization method for predicting diopter adjustment value in SMILE (full femtosecond laser) refractive surgery, in particular to an optimization method for predicting diopter adjustment value in SMILE refractive surgery based on a machine learning method, and at the same time involves realizing the optimization method system. Background technique [0002] Myopia has gradually become a global problem. Surveys and studies have shown that more than 1.5 billion people around the world suffer from myopia. In China, the prevalence of myopia among teenagers aged 15-25 is over 75%. Corneal refractive surgery (excimer laser surgery, femtosecond laser surgery) to treat refractive errors such as myopia, hyperopia and astigmatism is one of the latest common eye surgeries in this century. SMILE refractive surgery is a newly developed surgical technique for the treatment of refractive errors, and its effect and safety are great...

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Application Information

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IPC IPC(8): G16H50/70G06K9/62
CPCG16H50/70G06F18/214
Inventor 季书帆李炎郑承浩石林川崔彤张琳王书航徐佳慧
Owner 季书帆
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