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A new approach based on Machine Learning for predicting corneal curvature (K1) and astigmatism in patients with keratoconus after intracorneal ring implantation

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A new approach based on Machine Learning for predicting corneal curvature (K1) and astigmatism in patients with keratoconus after intracorneal ring implantation

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Valdés Mas, MA.; Martin-Guerrero, JD.; Rupérez Moreno, MJ.; Pastor, F.; Dualde, C.; Monserrat, C.; Peris-Martinez, C. (2014). A new approach based on Machine Learning for predicting corneal curvature (K1) and astigmatism in patients with keratoconus after intracorneal ring implantation. Computer Methods and Programs in Biomedicine. 116(1):39-47. doi:10.1016/j.cmpb.2014.04.003

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Title: A new approach based on Machine Learning for predicting corneal curvature (K1) and astigmatism in patients with keratoconus after intracorneal ring implantation
Author:
UPV Unit: Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà
Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
Keratoconus (KC) is the most common type of corneal ectasia. A corneal transplantation was the treatment of choice until the last decade. However, intra-corneal ring implantation has become more and more common, and it ...[+]
Subjects: Machine Learning , Keratoconus , Intracorneal rings , Astigmatism
Copyrigths: Cerrado
Source:
Computer Methods and Programs in Biomedicine. (issn: 0169-2607 )
DOI: 10.1016/j.cmpb.2014.04.003
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.cmpb.2014.04.003
Thanks:
This work was supported by the Spanish Ministry of Science and Innovation, MICINN (reference TIN2010-20999-C04-01).
Type: Artículo

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