Data generation algorithm. حسب Aluwani Ramalata (21262977)

Genetic Algorithm IQA Data حسب Michael Anastasios Mardikes (21762611)

الموضوعات: "…Modelling and simulation…"

Comparison of the EODA algorithm with existing algorithms in terms of recall. حسب Sunil Kumar (102321)

الموضوعات:

Comparison of the EODA algorithm with existing algorithms in terms of precision. حسب Sunil Kumar (102321)

الموضوعات:

Comparison of the EODA algorithm with existing algorithms in terms of F1-Score. حسب Sunil Kumar (102321)

الموضوعات:

Model-relevant variable data for external patients. حسب Lei Gao (6566)

The relevant code in the manuscript can be found in the supporting information data file. حسب Xini Fang (20861990)

الموضوعات:

The proposed algorithm of the outlier detection method. حسب Sunil Kumar (102321)

الموضوعات:

Structure of the Kuhn-Munkres Algorithm. حسب Qingnan Ji (22662198)

الموضوعات:

Ranking of ML algorithms. حسب Yasemin Ayaz Atalan (21989402)

"…The RF algorithm performed best with the lowest mean absolute percentage error (MAPE, 0.084%), mean absolute error (MAE, 0.035), root mean square error (RMSE, 0.063), and mean squared error (MSE, 0.004) values in the test dataset. …"

The AUC of each model was calculated using 113 ML algorithm. حسب Xuefen Lin (17785367)

الموضوعات:

Relevant data underlying the findings described in manuscript. حسب Lin Qi (128224)

User satisfaction scores for different algorithms. حسب Qingnan Ji (22662198)

الموضوعات:

Performance of models by different algorithms. حسب Yong Zhang (5893)

الموضوعات:

The overview of the ML algorithms’ flowchart. حسب Yasemin Ayaz Atalan (21989402)

"…The RF algorithm performed best with the lowest mean absolute percentage error (MAPE, 0.084%), mean absolute error (MAE, 0.035), root mean square error (RMSE, 0.063), and mean squared error (MSE, 0.004) values in the test dataset. …"

Performance of different machine learning algorithms. حسب Apichat Suratanee (634281)

Data Sheet 1_Algorithmic esthetics meets human intuition: the synergy of innovation and relevance shapes sustained attention.pdf حسب Wen Guan (5612195)

Illustration of the Noisy Student algorithm proposed by [30]. حسب Martin Wutke (19786999)

RFEcv algorithm flowchart. حسب Xinrui Wang (488330)

Variables tested in the ML algorithms. حسب Gilson Yuuji Shimizu (19837946)

"…Shapley values for local interpretability were more informative than LIME ones, which is in line with our exploratory analysis and global interpretation of the final model. Machine learning algorithms with good generalization and accompanied by interpretability analyses are recommended for assessments of individual risks of cardiovascular diseases and development of personalized preventive actions.…"