Comptes Rendus
Evaluation of hip fracture risk using a hyper-parametric model based on the Locally Linear Embedding technique
Comptes Rendus. Mécanique, Volume 347 (2019) no. 11, pp. 856-862.

The hip fracture is one of the most common diseases for elder people and also, one of the most worrying one since it usually is the starting point of further complications for both, the health of the patient and their daily life. Additionally, reports shown that there exist differences between people living in different regions, thus limiting the use of global models. In this work we propose a hip fracture prediction tool for a local region, using clinical data of the population of that region. The data is processed with a dimensionality reduction tool in combination with and hyper-parametrization process and the corresponding hyper-parameter optimization process for obtaining good predictions in the diagnoses, as the results shown.

Received:
Accepted:
Published online:
DOI: 10.1016/j.crme.2019.11.010
Keywords: Machine Learning, Fracture risk, Osteoporosis, Locally Linear Embedding, Hyper-parametrization, Optimization

Enrique Nadal 1; David Muñoz 1; Nieves Vivó 2; Irene Lucas 3; Juan José Ródenas 1

1 Centro de Investigación en Ingeniería Mecánica (CIIM), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
2 Hospital Virgen de los Lirios, Alcoy, Spain
3 Centro de Salud La Fábrica, Alcoy, Spain
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     journal = {Comptes Rendus. M\'ecanique},
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Enrique Nadal; David Muñoz; Nieves Vivó; Irene Lucas; Juan José Ródenas. Evaluation of hip fracture risk using a hyper-parametric model based on the Locally Linear Embedding technique. Comptes Rendus. Mécanique, Volume 347 (2019) no. 11, pp. 856-862. doi : 10.1016/j.crme.2019.11.010. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.1016/j.crme.2019.11.010/

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