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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.
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Hernandez C, Vilaplana V, Combalia M, García S, Podlipnik S, Burgos J, et al.. Sentinel lymph node status prediction with self-attention neural networks using histologies of primary melanoma tumours. In European Association of Dermato Oncology (EADO 2022). In Press.
Hernandez C, Combalia M, Malvehy J, Vilaplana V. Sentinel lymph node status prediction using self-attention networks and contrastive learning from routine histology images of primary tumours. In Medical Imaging with Deep Learning MIDL 2022. In Press.
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Podlipnik S, Hernandez C, Kiroglu A, García S, Ficapal J, Burgos J, et al.. Personalized medicine in melanoma patients aided by artificial intelligence. In Clinical Translation of Medical Image Computing and Computer Assisted Interventions (CLINICCAI) Workshop at MICCAI. 2021.
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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, 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, 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.
Catà M, Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Masked V-Net: an approach to brain tumor segmentation. In Multimodal Brain Tumor Segmentation Benchmark, Brain-lesion Workshop, MICCAI 2017 . 2017.
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Hernandez C, Kiroglu A, García S, Ficapal J, Burgos J, Podlipnik S, et al.. Implementation of personalized medicine in cutaneous melanoma patients aided by artificial intelligence. In 10th World Congress of2 Melanoma / 17th EADO Congress. 2021.
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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.
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Tarrés L. Clasificación de lesiones de piel con un ensemble de redes neuronales residuales. Vilaplana V, Combalia M. 2019.
Pelegrí JBustos. Clasificación de imágenes histológicas mediante redes neuronales convolucionales. Combalia M, Vilaplana V. 2018.
Casamitjana A, Catà M, Sánchez I, Combalia M, Vilaplana V. Cascaded V-Net Using ROI Masks for Brain Tumor Segmentation. In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2017. Crimi A., Bakas S., Kuijf H., Menze B., Reyes M. (eds). Cham: Springer; 2018. pp. 381-391.
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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.
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Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Augmented V-Net for White Matter Hyperintensities segmentation. In WMH Segmentation Challenge, Brain-lesion Workshop, MICCAI 2017 . 2017.
Casamitjana A, Sánchez I, Combalia M, Vilaplana V. Augmented V-Net for infant brain segmentation. In MICCAI Grand Challenge on 6-month Infant Brain MRI Segmentation, MICCAI 2017. 2017.
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). In Press.