AI Learning Model for Anterior Chamber Angle Prediction
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Solution Overview
Problem
Current methods for predicting the anterior chamber angle during lens implantation surgery lack effectiveness, leading to potential complications such as increased intraocular pressure or cataracts, highlighting the need for a more accurate and reliable prediction method.
Innovation Solution
A learning model is trained using historical data from lens implantation procedures to predict the postoperative anterior chamber angle based on input data including lens size and examination data, such as pupil size, anterior chamber depth, and preoperative angles, to determine the appropriate lens size for surgery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to determine lens size for implantation, then the surgical procedure can be performed, but the prediction of anterior chamber angle is inaccurate leading to potential complications
Solution Approach 1:
The patent replaces traditional mechanical measurement methods with an AI-based image processing system. The learning model automatically analyzes anterior segment images to predict postoperative anterior chamber angle, substituting manual measurement and estimation with automated computational analysis, thereby improving both measurement precision and surgical outcome reliability
Solution Approach 2:
The patent introduces new predictive parameters including preoperative anterior chamber angle, lens position, lens power, and crystalline lens status. By incorporating multiple parameters into the learning model rather than relying on single measurements, the system achieves more accurate predictions of postoperative anterior chamber angle, resolving the contradiction between measurement precision and reliability
2Productivity
If lens implantation is performed without accurate prediction, then the surgery can proceed, but side effects such as increased intraocular pressure or cataracts may occur
Solution Approach 1:
The patent performs preliminary prediction of the postoperative anterior chamber angle before lens implantation surgery. By using the learning model to forecast outcomes in advance, surgeons can select appropriate lens parameters and anticipate potential complications, enabling preventive measures to be taken before surgery while maintaining surgical efficiency
Solution Approach 2:
The patent establishes a feedback mechanism where the learning model continuously improves its prediction accuracy by incorporating actual surgical outcomes. The system uses historical data from previous surgeries to refine its predictions, creating a closed-loop system that reduces side effects while maintaining high surgical efficiency through increasingly accurate predictions
Data Source
AI summary
A method of predicting the anterior chamber angle of the eye of a surgical candidate for lens implantation according to an embodiment of the present invention includes obtaining input data including a lens size, obtaining a predicted postoperative anterior chamber angle based on a learning model using the input data. The learning model may be trained based on the lens size and the measured postoperative anterior chamber angle of a plurality of patients who have undergone the lens implantation in the past.