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基于人工智能的不同人工晶状体计算公式准确性的比较。

Comparison of accuracy of different intraocular lens power calculation methods using artificial intelligence.

机构信息

Borsod-Abaúj-Zemplén County Hospital and University Teaching Hospital, Miskolc, Hungary.

Department of Ophthalmology, University of Debrecen, Debrecen, Hungary.

出版信息

Eur J Ophthalmol. 2022 Jan;32(1):235-241. doi: 10.1177/1120672121994720. Epub 2021 Feb 17.

Abstract

PURPOSE

To assess the accuracy of the intraocular lens (IOL) power calculation based on three methods using artificial intelligence (AI) and one formula using no AI.

METHODS

During cataract surgery on 114 eyes, one type of IOL was implanted, calculated with the Hill-RBF 2.0 method. The theoretical postoperative refractions were calculated using the Kane and the Pearl-DGS methods and a vergence based formula (Barrett Universal II, BUII). The differences between the manifest and objective postoperative refractions and the predicted refractions were calculated. The percentage of eyes within ±0.5 D and ±1.0 D prediction error (PE), the mean, and the median absolute errors (MAE and MedAE) were also determined.

RESULTS

The mean age of the patients was 69.48 years; the axial length was between 21.19 and 25.39 mm. The number of eyes within ±0.5/±1.0 D PE was 96/108 (84.21%/94.73%) using the Hill-RBF 2.0 method, 92/107 (80.70%/93.85%) with the Kane method, 91/107 (79.82%/93.85%) with the Pearl-DGS method, and 91/106 (79.82%/92.98%) with the BUII formula, using subjective refraction. With objective refractometric data, PEs were within ±0.5 D in 88 (77.19%), 83 (72.80%), 82 (71.92%), and 80 (70.17%) cases (Hill-RBF, Kane, Pearl-DGS, BUII, respectively). MAE and MedAE were also best with the Hill-RBF 2.0 method (0.3 D; 0.18 D).

CONCLUSION

Better accuracy of PE might be obtained by the Hill-RBF 2.0 method compared with BUII. The Kane and Pearl-DGS methods showed similar accuracy when compared with BUII.

摘要

目的

评估基于人工智能 (AI) 的三种方法和一种不使用 AI 的公式计算人工晶状体 (IOL) 屈光力的准确性。

方法

在 114 只眼中进行白内障手术,植入一种 IOL,使用 Hill-RBF 2.0 方法计算理论术后屈光度数。使用 Kane 和 Pearl-DGS 方法以及基于散焦的公式(Barrett Universal II,BUII)计算理论术后屈光度数。计算实际术后屈光度数与客观术后屈光度数和预测屈光度数之间的差异。还确定了预测误差 (PE) 在 ±0.5 D 和 ±1.0 D 范围内的眼数百分比、平均值和中位数绝对误差 (MAE 和 MedAE)。

结果

患者平均年龄为 69.48 岁;眼轴长度在 21.19 至 25.39 mm 之间。使用 Hill-RBF 2.0 方法,PE 在 ±0.5/±1.0 D 范围内的眼数分别为 96/108(84.21%/94.73%),Kane 方法为 92/107(80.70%/93.85%),Pearl-DGS 方法为 91/107(79.82%/93.85%),BUII 公式为 91/106(79.82%/92.98%),均采用主观屈光度数。使用客观屈光测量数据,PE 在 ±0.5 D 范围内的眼数分别为 88(77.19%)、83(72.80%)、82(71.92%)和 80(70.17%)(Hill-RBF、Kane、Pearl-DGS、BUII 分别)。MAE 和 MedAE 也以 Hill-RBF 2.0 方法为最佳(0.3 D;0.18 D)。

结论

与 BUII 相比,Hill-RBF 2.0 方法可能获得更好的 PE 准确性。Kane 和 Pearl-DGS 方法与 BUII 相比具有相似的准确性。

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