• John Arevalo, Fabio A González, Raúl Ramos-Pollán, Jose L. Oliveira and Miguel Angel Guevara Lopez. Representation learning for mammography mass lesion classification with convolutional neural networks.In Computer methods and programs in biomedicine, pages 248 - 257. Elsevier, 2016. [pdf] [code]

  • John Arevalo, Angel Cruz-Roa, Viviana Arias, Eduardo Romero, and Fabio A. González. An unsupervised feature learning framework for basal cell carcinoma image analysis. In Artificial Intelligence in Medicine , pages 131 - 145. Elsevier, 2015.

  • Angel Cruz-Roa, John Arevalo, Ajay Basavanhally, Anant Madabhushi, and Fabio González. A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation. In Eduardo Romero and Natasha Lepore, editors, 10th International Symposium on Medical Information Processing and Analysis. SPIE, jan 2015.

  • Jorge A. Vanegas, John Arevalo, Sebastian Otálora, Fabián Páez, Santiago A. Pérez-Rubiano, and Fabio A González. Mindlab at imageclef 2014: Scalable concept image annotation. In CLEF 2014 Evaluation Labs and Workshop, Online Working Notes, Sheffield, UK, september 2014.

  • John Arevalo, Raúl Ramos-Pollan, and Fabio A. González. Distributed cache strategies for machine learning classification tasks over cluster computing resources. In Gonzalo Hernández, Carlos Jaime Barrios Hernández, Gilberto Díaz, Carlos García Garino, Sergio Nesmachnow, Tomás Pérez-Acle, Mario Storti, and Mariano Vázquez, editors, High Performance Computing, volume 485 of Communications in Computer and Information Science, pages 43–53. Springer Berlin Heidelberg, Valparaiso, Chile, 2014.

  • John Arevalo. Representation learning for histopathology image analysis. Master’s thesis, Universidad Nacional de Colombia, Bogotá, Colombia, 2013.

  • Angel Cruz-Roa, John Arevalo, Anant Madabhushi, and Fabio A. González Osorio. A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection. In Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot, and Nassir Navab, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, volume 8150 of Lecture Notes in Computer Science, pages 403–410. Springer Berlin Heidelberg, 2013.

  • John Arevalo, Angel Cruz-Roa, and Fabio A. González. Hybrid image representation learning model with invariant features for basal cell carcinoma detection. In Jorge Brieva and Boris Escalante-Ramírez, editors, IX International Seminar on Medical Information Processing and Analysis, Mexico City, Mexico, nov 2013. SPIE.

  • Andrea Rueda, John Arevalo, Angel Cruz-Roa, Eduardo Romero, and Fabio A. González. Bag of features for automatic classification of alzheimer’s disease in magnetic resonance images. In Luis Alvarez, Marta Mejail, Luis Gomez, and Julio Jacobo, editors, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, volume 7441 of Lecture Notes in Computer Science, pages 559–566. Springer Berlin Heidelberg, Buenos Aires, Argentina, 2012.

  • Angel Cruz-Roa, John Arevalo, and Fabio González. Prediction of morphometric measures from bag-of-features image representation of cervix cancer cells. In 8th International Seminar on Medical Information Processing and Analysis, San Cristobal, Venezuela, 2012.