Search Publication
Export 12 results:
Author Title [ Type] Year Filters: Author is Carlos Hernandez [Clear All Filters]
Interpreting Machine Learning Models for Survival Analysis: A Study of Cutaneous Melanoma Using the SEER Database. In Explainable Artificial Intelligence and Process Mining Applications for Healthcare,. Springer, Cham; 2024.
. Artificial intelligence to predict positivity of sentinel lymph node biopsy in melanoma patients. In European Association of Dermato Oncology (EADO 2022). 2022.
. Breast Cancer Molecular Subtyping from H&E Whole Slide Images using Foundation Models and Transformers. In Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care, MICCAI 2024. In Press.
. Bridging Domains in Melanoma Diagnostics: Predicting BRAF Mutations and Sentinel Lymph Node Positivity with Attention-Based Models in Histological Images. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (DEF-AI-MIA workshop). 2024.
. Contrastive and attention-based multiple instance learning for the prediction of sentinel lymph node status from histopathologies of primary melanoma tumours. In Cancer Prevention through early detecTion (Caption) Workshop at 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022). 2022.
. Implementation of personalized medicine in cutaneous melanoma patients aided by artificial intelligence. In 10th World Congress of2 Melanoma / 17th EADO Congress. 2021.
. Interpreting Machine Learning models for Survival Analysis: A study of Cutaneous Melanoma using the SEER Database. In XAI-Healthcare 2023 Workshop at 21st International Conference of Artificial Intelligence in Medicine (AIME 2023). Portoroz, Slovenia; 2023.
. 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.
. 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. 2022.
. Sentinel lymph node status prediction with self-attention neural networks using histologies of primary melanoma tumours. In European Association of Dermato Oncology (EADO 2022). 2022.
. Bcn20000: Dermoscopic lesions in the wild. Nature - Scientific Data. 2024;11.
. SurvLIMEpy: A Python package implementing SurvLIME. Expert Systems With Applications. 2024;237, Part C.
.