Výsledky vyhledávání - "Acha, Begona"

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AI-Driven Skin Cancer Diagnosis: Grad-CAM and Expert Annotations for Enhanced Interpretability

Autor: Matas, Iván, Serrano, Carmen, Silva, Francisca, Serrano, Amalia, Toledo-Pastrana, Tomás, Acha, Begoña

An AI tool has been developed to provide interpretable support for the diagnosis of BCC via teledermatology, thus speeding up referrals and optimizing resource utilization. The interpretability is provided in two ways: on the one hand, the main BCC d

Externí odkaz: http://arxiv.org/abs/2407.00104

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Concordance in basal cell carcinoma diagnosis. Building a proper ground truth to train Artificial Intelligence tools

Autor: Silva-Clavería, Francisca, Serrano, Carmen, Matas, Iván, Serrano, Amalia, Toledo-Pastrana, Tomás, Moreno-Ramírez, David, Acha, Begoña

Background: The existence of different basal cell carcinoma (BCC) clinical criteria cannot be objectively validated. An adequate ground-truth is needed to train an artificial intelligence (AI) tool that explains the BCC diagnosis by providing its der

Externí odkaz: http://arxiv.org/abs/2406.18240

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Robust Melanoma Thickness Prediction via Deep Transfer Learning enhanced by XAI Techniques

Autor: Nogales, Miguel, Acha, Begoña, Alarcón, Fernando, Pereyra, José, Serrano, Carmen

This study focuses on analyzing dermoscopy images to determine the depth of melanomas, which is a critical factor in diagnosing and treating skin cancer. The Breslow depth, measured from the top of the granular layer to the deepest point of tumor inv

Externí odkaz: http://arxiv.org/abs/2406.13441

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