Listar por autor "Cernea Corbeanu, Ana"

Addressing noise and estimating uncertainty in biomedical data through the exploration of chemical space

Andrés Galiana, Enrique Juan de

; Fernández Martínez, Juan Luis

; Fernández Brillet, L.; Cernea Corbeanu, Ana

; Kloczkowski, A. (2022)

Aligned PSO for optimization of image processing methods applied to the face recognition problem

Fernández Martínez, Juan Luis

; Cernea Corbeanu, Ana

; García Gonzalo, María Esperanza

; Velasco Valdés, Julián

; Panigrahi, B. K. (2013)

Automatic Classification of Cell Patterns for Triple Negative Breast Cancer Identification

Fernández Martínez, Juan Luis

; Cernea Corbeanu, Ana

; Andrés Galiana, Enrique Juan de

(International Academy, Research, and Industry Association, 2014)

Comparison of Different Sampling Algorithms for Phenotype Prediction

Cernea Corbeanu, Ana

; Fernández Martínez, Juan Luis

; Andrés Galiana, Enrique Juan de

; Fernández Ovies, Francisco Javier

; Fernández Muñiz, María Zulima

; Álvarez Machancoses, Óscar; Saligan, L.; Sonis, S. T. (2018)

Comparison of three mathematical models for COVID-19 prediction

Martínez Fernández, Pelayo; Fernández Muñiz, María Zulima

; Cernea Corbeanu, Ana

; Fernández Martínez, Juan Luis

; Kloczkowski, A. (2023)

Deep neural networks for phenotype prediction in rare diseases inclusion body myositis: a case study

Andrés Galiana, Enrique Juan de

; Fernández Ovies, Francisco Javier

; Cernea Corbeanu, Ana

; Fernández Martínez, Juan Luis

; Kloczkowski, Andrzej (2020)

Detection of Breast Cancer Using Infrared Thermography and Deep Neural Networks

Fernández Ovies, Francisco Javier

; Santiago Alférez-Baquero, E.; Andrés Galiana, Enrique Juan de

; Cernea Corbeanu, Ana

; Fernández Muñiz, María Zulima

; Fernández Martínez, Juan Luis

(2019)

Efficient uncertainty analysis of the 3D electrical tomography inverse problem

Fernández Martínez, Juan Luis

; Fernández Muñiz, María Zulima

; Xu, S.; Cernea Corbeanu, Ana

; Sirieix, C.; Riss, J. (2019)

Exploring the uncertainty space of ensemble classifiers in face recognition

Fernández Martínez, Juan Luis

; Cernea Corbeanu, Ana

(2015)

Four-Points Particle Swarm Optimization Algorithms

García Gonzalo, María Esperanza

; Fernández Martínez, Juan Luis

; Cernea Corbeanu, Ana

(2014)

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm

Reinbolt, R. E.; Sonis, Stephen T.; Timmers, C. D.; Fernández Martínez, Juan Luis

; Cernea Corbeanu, Ana

; Andrés Galiana, Enrique Juan de

; Hashemi, S.; Miller, K.; Pilarski, R.; Lustberg, M. B. (2017)

How to deal with uncertainty in inverse and classification problems

Fernández Martínez, Juan Luis

; Fernández Muñiz, María Zulima

; Cernea Corbeanu, Ana

; Pallero, J. L. G.; Andrés Galiana, Enrique Juan de

; Pedruelo González, Luis Mariano

; Álvarez, Óscar; Fernández Ovies, Francisco Javier

(2020)

Image indexing optimization. Biometric and biomedical applications

Cernea Corbeanu, Ana

(2014-11-07)

Improvements in resampling techniques for phenotype prediction: Applications to neurodegenerative diseases

Beltrán Vargas, Juan Carlos; Andrés Galiana, Enrique Juan de

; Cernea Corbeanu, Ana

; Fernández Martínez, Juan Luis

(2017)

Innovations in genomics and big data analytics for personalized medicine and health care: a review

Hassan, M.; Awan, F. M.; Naz, A.; Andrés Galiana, Enrique Juan de

; Álvarez Machancoses, Óscar; Cernea Corbeanu, Ana

; Fernández Brillet, L.; Fernández Martínez, Juan Luis

; Kloczkowski, A. (2022)

Linear inversion via the discrete wavelet transform pseudoinverse

Fernández Muñiz, María Zulima

; Cernea Corbeanu, Ana

; Fernández Martínez, Juan Luis

(2017)

MMP11 expression in intratumoral inflammatory cells in breast cancer

Eiró Díaz, Noemí; Cid, Sandra; Fernández, Berta; Fraile, María; Cernea Corbeanu, Ana

; Sánchez, Rosario; Andicoechea, Alejandro; Andrés Galiana, Enrique Juan de

; González Vázquez, Luis Ovidio

; Fernández Muñiz, María Zulima

; Fernández Martínez, Juan Luis

; Vizoso Piñeiro, Francisco José

(2019)

Numerical analysis and comparison of spectral decomposition methods in biometric applications

Fernández Martínez, Juan Luis

; Cernea Corbeanu, Ana

(World Scientific Publishing, 2014)

Objetos de aprendizaje 2.0: Una nueva generación de contenidos en contextos conectivistas

Moral Pérez, María Esther del

; Cernea Corbeanu, Ana

; Villalustre Martínez, Lourdes

(2010)

On the role of artificial intelligence in genomics to enhance precision medicine

Álvarez Machancoses, Óscar; Andrés Galiana, Enrique Juan de

; Cernea Corbeanu, Ana

; Fernández de la Viña, J.; Fernández Martínez, Juan Luis

(2020)

Listar por autor "Cernea Corbeanu, Ana"

Addressing noise and estimating uncertainty in biomedical data through the exploration of chemical space ﻿

Aligned PSO for optimization of image processing methods applied to the face recognition problem ﻿

Automatic Classification of Cell Patterns for Triple Negative Breast Cancer Identification ﻿

Comparison of Different Sampling Algorithms for Phenotype Prediction ﻿

Comparison of three mathematical models for COVID-19 prediction ﻿

Deep neural networks for phenotype prediction in rare diseases inclusion body myositis: a case study ﻿

Detection of Breast Cancer Using Infrared Thermography and Deep Neural Networks ﻿

Efficient uncertainty analysis of the 3D electrical tomography inverse problem ﻿

Exploring the uncertainty space of ensemble classifiers in face recognition ﻿

Four-Points Particle Swarm Optimization Algorithms ﻿

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm ﻿

How to deal with uncertainty in inverse and classification problems ﻿

Image indexing optimization. Biometric and biomedical applications ﻿

Improvements in resampling techniques for phenotype prediction: Applications to neurodegenerative diseases ﻿

Innovations in genomics and big data analytics for personalized medicine and health care: a review ﻿

Linear inversion via the discrete wavelet transform pseudoinverse ﻿

MMP11 expression in intratumoral inflammatory cells in breast cancer ﻿

Numerical analysis and comparison of spectral decomposition methods in biometric applications ﻿

Objetos de aprendizaje 2.0: Una nueva generación de contenidos en contextos conectivistas ﻿

On the role of artificial intelligence in genomics to enhance precision medicine ﻿

Addressing noise and estimating uncertainty in biomedical data through the exploration of chemical space

Aligned PSO for optimization of image processing methods applied to the face recognition problem

Automatic Classification of Cell Patterns for Triple Negative Breast Cancer Identification

Comparison of Different Sampling Algorithms for Phenotype Prediction

Comparison of three mathematical models for COVID-19 prediction

Deep neural networks for phenotype prediction in rare diseases inclusion body myositis: a case study

Detection of Breast Cancer Using Infrared Thermography and Deep Neural Networks

Efficient uncertainty analysis of the 3D electrical tomography inverse problem

Exploring the uncertainty space of ensemble classifiers in face recognition

Four-Points Particle Swarm Optimization Algorithms

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm

How to deal with uncertainty in inverse and classification problems

Image indexing optimization. Biometric and biomedical applications

Improvements in resampling techniques for phenotype prediction: Applications to neurodegenerative diseases

Innovations in genomics and big data analytics for personalized medicine and health care: a review

Linear inversion via the discrete wavelet transform pseudoinverse

MMP11 expression in intratumoral inflammatory cells in breast cancer

Numerical analysis and comparison of spectral decomposition methods in biometric applications

Objetos de aprendizaje 2.0: Una nueva generación de contenidos en contextos conectivistas

On the role of artificial intelligence in genomics to enhance precision medicine