Development and validation of predictive models for myopia onset and progression using extensive 15-year refractive data in children and adolescents

Zhao, Jing; Yu, Yanze; Li, Yiming; Li, Feng; Zhang, Zhe; Jian, Weijun; Chen, Zhi; Shen, Yang; Wang, Xiaoying; Ye, Zhengqiang; Huang, Chencui; Zhou, Xingtao

doi:10.1186/s12967-024-05075-0

Table 2 Regressive performance of the Random Forest and XGBoost algorithms

From: Development and validation of predictive models for myopia onset and progression using extensive 15-year refractive data in children and adolescents

Year	NSE required	Model	R²	Total		3–6 years		7–14 years		15–18 years
Year	NSE required	Model	R²	MAE	MSE	MAE	MSE	MAE	MSE	MAE	MSE
1	No	RF	0.958	0.360	0.364	0.408	0.441	0.331	0.441	0.369	0.343
1	No	XGBoost	0.992	0.078	0.099	0.077	0.112	0.078	0.075	0.091	0.345
2	No	RF	0.920	0.491	0.772	0.563	0.933	0.435	0.633	0.529	0.698
	No	XGBoost	0.952	0.397	0.657	0.472	0.850	0.332	0.474	0.336	0.489
	Yes	XGBoost	0.949	0.437	0.723	0.499	0.917	0.375	0.504	0.388	1.010
3	No	RF	0.886	0.619	1.176	0.682	1.361	0.581	0.992	0.619	1.484
	No	XGBoost	0.922	0.577	1.128	0.638	1.379	0.533	0.878	0.585	1.103
	Yes	XGBoost	0.930	0.588	1.063	0.652	1.324	0.527	0.781	0.570	0.880
4	No	RF	0.840	0.720	1.715	0.789	2.055	0.663	1.380	0.850	1.856
	No	XGBoost	0.896	0.704	1.540	0.758	1.776	0.647	1.282	0.693	1.931
	Yes	XGBoost	0.902	0.693	1.561	0.771	1.789	0.625	1.250	0.613	3.187
5	No	RF	0.829	0.619	1.814	0.733	2.139	0.557	1.487	0.570	2.306
	No	XGBoost	0.869	0.688	1.929	0.777	2.372	0.635	1.412	0.763	3.349
	Yes	XGBoost	0.889	0.678	1.753	0.767	2.116	0.618	1.357	0.669	1.269
6	No	RF	0.794	0.606	2.235	0.734	2.670	0.515	1.770	0.600	3.054
	No	XGBoost	0.860	0.679	2.133	0.789	2.508	0.581	1.631	0.935	4.247
	Yes	XGBoost	0.882	0.643	1.925	0.802	2.383	0.505	1.410	0.479	1.718
7	No	RF	0.785	0.554	2.375	0.778	2.968	0.442	1.783	0.394	2.059
	No	XGBoost	0.841	0.691	2.401	0.851	2.888	0.574	1.865	0.765	2.141
	Yes	XGBoost	0.867	0.650	2.237	0.830	2.858	0.495	1.572	0.535	1.422
8	No	RF	0.803	0.373	2.234	0.652	3.053	0.290	1.456	0.286	2.696
	No	XGBoost	0.842	0.479	2.431	0.697	3.201	0.369	1.683	0.425	2.373
	Yes	XGBoost	0.871	0.499	2.133	0.751	3.212	0.361	1.114	0.385	1.411
9	No	RF	0.810	0.341	2.177	0.522	3.263	0.281	1.241	0.284	2.768
	No	XGBoost	0.860	0.444	2.305	0.647	3.412	0.357	1.348	0.586	2.034
	Yes	XGBoost	0.877	0.427	2.148	0.641	3.075	0.328	1.115	0.326	3.517
10	No	RF	0.704	1.477	5.943	1.500	6.482	1.401	4.970	1.758	6.065
	No	XGBoost	0.726	1.371	5.510	1.530	6.356	1.168	4.184	1.108	3.622
	Yes	XGBoost	0.729	1.409	5.709	1.573	6.766	1.216	3.640	0.887	6.972
11	No	RF	0.629	1.602	7.290	1.602	7.791	1.536	5.708	2.768	13.966
	No	XGBoost	0.661	1.418	6.344	1.487	7.461	1.332	4.537	1.645	7.694
	Yes	XGBoost	0.786	1.498	4.749	1.600	5.155	1.360	4.023	1.735	5.062
12	No	RF	0.662	1.685	6.768	1.875	7.395	1.496	6.059	1.919	4.669
	No	XGBoost	0.679	1.589	6.421	1.825	7.329	1.341	5.358	1.270	3.824
	Yes	XGBoost	0.766	1.450	5.849	1.551	6.024	1.345	5.721	1.038	2.596
13	No	RF	0.618	1.450	8.662	1.939	9.005	1.393	8.268	2.696	8.597
	No	XGBoost	0.656	1.499	7.795	1.776	8.657	1.246	7.040	1.281	6.323
	Yes	XGBoost	0.758	1.611	6.370	1.874	7.900	1.431	4.602	1.061	2.131
14	No	RF	0.604	1.802	11.684	1.907	13.187	1.722	10.680	2.261	9.304
	No	XGBoost	0.613	1.673	11.410	1.975	13.151	1.579	10.820	1.653	5.915
	Yes	XGBoost	0.808	1.424	4.603	1.652	5.377	1.177	4.128	0.546	0.537

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