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Using Artificial Intelligence and Novel Polynomials to Predict Subjective Refraction

This work aimed to use artificial intelligence to predict subjective refraction from wavefront aberrometry data processed with a novel polynomial decomposition basis. Subjective refraction was converted to power vectors (M, J0, J45). Three gradient boosted trees (XGBoost) algorithms were trained to...

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Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Cyhoeddwyd yn:Sci Rep
Prif Awduron: Rampat, Radhika, Debellemanière, Guillaume, Malet, Jacques, Gatinel, Damien
Fformat: Artigo
Iaith:Inglês
Cyhoeddwyd: Nature Publishing Group UK 2020
Pynciau:
Mynediad Ar-lein:https://ncbi.nlm.nih.gov/pmc/articles/PMC7244728/
https://ncbi.nlm.nih.gov/pubmed/32444650
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-65417-y
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