| 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 | 2292 | 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 | 624 | 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 | 529 | 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 | 242 | 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 | 111 | 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 | 95 | 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 | 88 | 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 | 87 | 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 | 62 | 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 |
| 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 |
| 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 | 32 | 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 | 25 | 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 | 23 | 2021 |
| Digitally stained confocal microscopy through deep learning M Combalia Escudero, J Pérez Ankar, A García Herrera, L Alos, ... International Conference on Medical Imaging with Deep Learning: 8-10 July …, 2019 | 19 | 2019 |
| 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 |
| Application of distributed computing and machine learning technologies to cybersecurity H Attak, M Combalia, G Gardikis, B Gastón, L Jacquin, A Litke, ... Computer & Electronics Security Applications Rendez-vous (C&ESAR), Rennes, 2018., 2018 | 17 | 2018 |
| 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 | 17 | 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 | 17 | 2017 |
| Bcn20000: Dermoscopic lesions in the wild C Hernández-Pérez, M Combalia, S Podlipnik, NCF Codella, ... Scientific data 11 (1), 641, 2024 | 16 | 2024 |
