| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2132 | 2018 |
| Bcn20000: Dermoscopic lesions in the wild M Combalia, NCF Codella, V Rotemberg, B Helba, V Vilaplana, O Reiter, ... arXiv preprint arXiv:1908.02288, 2019 | 596 | 2019 |
| A patient-centric dataset of images and metadata for identifying melanomas using clinical context V Rotemberg, N Kurtansky, B Betz-Stablein, L Caffery, E Chousakos, ... Scientific data 8 (1), 34, 2021 | 504 | 2021 |
| Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts S Haggenmüller, RC Maron, A Hekler, JS Utikal, C Barata, RL Barnhill, ... European Journal of Cancer 156, 202-216, 2021 | 233 | 2021 |
| Checklist for evaluation of image-based artificial intelligence reports in dermatology: CLEAR derm consensus guidelines from the international skin imaging collaboration … R Daneshjou, C Barata, B Betz-Stablein, ME Celebi, N Codella, ... JAMA dermatology 158 (1), 90-96, 2022 | 106 | 2022 |
| Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge M Combalia, N Codella, V Rotemberg, C Carrera, S Dusza, D Gutman, ... The Lancet Digital Health 4 (5), e330-e339, 2022 | 98 | 2022 |
| Powering the Internet of Things through light communication I Demirkol, D Camps-Mur, J Paradells, M Combalia, W Popoola, H Haas IEEE Communications Magazine 57 (6), 107-113, 2019 | 87 | 2019 |
| Uncertainty estimation in deep neural networks for dermoscopic image classification M Combalia, F Hueto, S Puig, J Malvehy, V Vilaplana Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 85 | 2020 |
| Cascaded V-Net using ROI masks for brain tumor segmentation A Casamitjana, M Catà, I Sánchez, M Combalia, V Vilaplana International MICCAI Brainlesion Workshop, 381-391, 2017 | 67 | 2017 |
| Basal cell carcinoma characterization using fusion ex vivo confocal microscopy: a promising change in conventional skin histopathology J Pérez‐Anker, S Ribero, O Yélamos, A García‐Herrera, L Alos, B Alejo, ... British Journal of Dermatology 182 (2), 468-476, 2020 | 54 | 2020 |
| A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Sci Data 8, 34 (2021) V Rotemberg, N Kurtansky, B Betz-Stablein, L Caffery, E Chousakos, ... | 48 | |
| BCN20000: Dermoscopic lesions in the wild. arXiv 2019 M Combalia, NC Codella, V Rotemberg, B Helba, V Vilaplana, O Reiter, ... arXiv preprint arXiv:1908.02288, 1908 | 47 | 1908 |
| BCN20000: dermoscopic lesions in the wild (2019) M Combalia, NC Codella, V Rotemberg, B Helba, V Vilaplana, O Reiter, ... arXiv preprint arXiv:1908.02288, 1908 | 34 | 1908 |
| Position statement of the EADV Artificial Intelligence (AI) Task Force on AI‐assisted smartphone apps and web‐based services for skin disease TE Sangers, H Kittler, A Blum, RP Braun, C Barata, A Cartocci, ... Journal of the European Academy of Dermatology and Venereology 38 (1), 22-30, 2024 | 29 | 2024 |
| New regulation of medical devices in the EU: impact in dermatology J Malvehy, R Ginsberg, L Sampietro‐Colom, J Ficapal, M Combalia, ... Journal of the European Academy of Dermatology and Venereology 36 (3), 360-364, 2022 | 24 | 2022 |
| Deep learning automated pathology in ex vivo microscopy M Combalia, S Garcia, J Malvehy, S Puig, AG Mülberger, J Browning, ... Biomedical Optics Express 12 (6), 3103-3116, 2021 | 21 | 2021 |
| Machine learning in melanoma diagnosis. Limitations about to be overcome C González-Cruz, MA Jofre, S Podlipnik, M Combalia, D Gareau, ... Actas Dermo-Sifiliográficas (English Edition) 111 (4), 313-316, 2020 | 18 | 2020 |
| Monte-Carlo sampling applied to multiple instance learning for histological image classification M Combalia, V Vilaplana International Workshop on Deep Learning in Medical Image Analysis, 274-281, 2018 | 18 | 2018 |
| Masked V-Net: an approach to brain tumor segmentation M Catà, A Casamitjana Díaz, I Sanchez Muriana, M Combalia, ... 2017 International MICCAI BraTS Challenge. Pre-conference proceedings, 42-49, 2017 | 18 | 2017 |
| Digitally stained confocal microscopy through deep learning M Combalia, J Pérez-Anker, A García-Herrera, L Alos, V Vilaplana, ... | 17 | 2019 |
