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Cumplido-Mayoral I, Shekari M, Salvadó G, Operto G, Cacciaglia R, Falcon C, et al.. Brain structural alterations in cognitively unimpaired individuals with discordant amyloid-β PET and CSF Aβ42 status: findings using Machine Learning. In Alzheimer's Association International Conference. 2021.
Cumplido-Mayoral I, Mila-Aloma M, Falcon C, Cacciaglia R, Minguillon C, Fauria K, et al.. Brain-age prediction and its associations with glial and synaptic CSF markers. In Alzheimer's Association International Conference. Amsterdam, Netherlands; 2023.
Cumplido-Mayoral I, Salvadó G, Shekari M, Falcon C, Alomà MMilà, Baizán ANiñerola, et al.. Machine learning on combined neuroimaging and plasma biomarkers for triaging participants of secondary prevention trials in Alzheimer’s Disease. In Alzheimer's Association International Conference. 2021.
Cumplido-Mayoral I, Mila-Aloma M, Lorenzini L, Wink AMeije, Mutsaerts H, Haller S, et al.. Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex. In 15th Clinical Trials on Alzheimer’s Disease Conference (CTAD). San Francisco, USA; 2022.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration stratified by sex. eLife. 2023;12.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration. In Alzheimer's Association International Conference. 2022.
Cuadras C, Valero S, Salembier P, Chanussot J. Some measures of multivariate association relating two spectral data sets. In 19th International Conference on Computational Statistics, COMSTAT 2010. Paris, France; 2010.
Cuadras C, Valero S, Cuadras D, Salembier P, Chanussot J. Distance-based measures of association with applications in relating hyperspectral images. Communications in Statistics - Theory and Method. 2012;41:2342–2355.  (296.22 KB)
Creus R, Nieto JJosé, Giró-i-Nieto X. PixelEDL: Unsupervised Skill Discovery and Learning from Pixels. In CVPR 2021 Embodied AI Workshop. 2021.  (1.55 MB)
Creus R. Unsupervised skill learning from pixels. Nieto JJosé, Giró-i-Nieto X. 2021.  (19.61 MB)
de Craene M, Macq B, Marqués F, Salembier P, Warfield S. Unbiased group-wise alignment by iterative central tendency estimations. Mathematical modeling of natural phenomena. 2008;3:2–32.
Cortés S. Interfaz gráfica de usuario para la búsqueda de imágenes basada en imágenes. Giró-i-Nieto X. 2009.  (2.84 MB)
Cortés S. GOS: búsqueda visual de imágenes. Giró-i-Nieto X, Marqués F. Buran. 2010 pp. 36–44. Report No.: 25.
Correa P, Marqués F, Marichal X, Macq B. 3D posture estimation using geodesic distance maps. Multimedia tools and applications. 2008;38:365–384.
Correa P, Czyz J, Umeda T, Marqués F, Marichal X, Macq B. Silhouette-based Probabilistic 2D Human Motion Estimation for Real-Time Applications. In IEEE International Conference on Image Processing. 2005. pp. 836–839.
Correa P. Dual morphology-based and Bayesian approach for markerless human motion capture in natural interaction environments. Marqués F, Macq B. Université Catholique de Louvain (UCL); 2006.
Correa P, Czyz J, Marqués F, Umeda T, Marichal X, Macq B. Bayesian approach for morphology based 2D human motion capture. IEEE transactions on multimedia. 2007;9:754–765.
Compri M. Multi-label Remote Sensing Image Retrieval based on Deep Features. Demir B, Giró-i-Nieto X. 2017.  (1.99 MB)
Combalia M, Vilaplana V. Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification. In Workshop on Deep Learning in Medical Image Analysis, MICCAI. Granada, Spain; 2018.
Combalia M, Hueto F, Puig S, Malvehy J, Vilaplana V. Uncertainty Estimation in Deep Neural Networks for Dermoscopic Image Classification. In CVPR 2020, ISIC Skin Image Analysis Workshop. 2020.
Combalia M, Codella NCF, Rotemberg V, Helba B, Vilaplana V, Reiter O, et al.. BCN20000: Dermoscopic Lesions in the Wild. In International Skin Imaging Collaboration (ISIC) Challenge on Dermoscopic Skin Lesion Analysis 2019. 2019.
Combalia M, Vilaplana V. Monte-Carlo Sampling applied to Multiple Instance Learning for Whole Slide Image Classification. In International Conference on Medical Imaging with Deep Learning. Amsterdam, The Netherlands; 2018.
Combalia M, Podlipnik S, Hernandez C, García S, Ficapal J, Burgos J, et al.. Artificial intelligence to predict positivity of sentinel lymph node biopsy in melanoma patients. In European Association of Dermato Oncology (EADO 2022). 2022.
Combalia M, Pérez-Anker J, García-Herrera A, Alos L, Vilaplana V, Marques F, et al.. Digitally Stained Confocal Microscopy through Deep Learning. In International Conference on Medical Imaging with Deep Learning (MIDL 2019). London; 2019.
Combalia M, Vilaplana V. Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification. In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support. Springer International Publishing; 2018. pp. 274-281.

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