Carmen Serrano

MultiTask learning AI system to assist BCC diagnosis with dual explanation

Iván Matas, Carmen Serrano, Francisca Silva, Amalia Serrano et autres

Basal cell carcinoma (BCC) accounts for 75% of all skin cancers. Currently, all major public hospitals in Spain have a dermatology care protocol that includes teledermatology. This has created an overload for hospital dermatologists, which could be alleviated with an AI tool …

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Radiomics-Based Characterization of Hematologic Toxicity in Lung-Cancer Radiotherapy

Guillermo Canterla, Begoña Acha, Manuel Borrego, José Luis López et autres

Concurrent chemoradiotherapy (CRT) is the standard treatment for locally advanced lung cancer, as it has been shown to improve survival outcomes. However, it is associated with increased toxicity rates, particularly hematologic toxicity, mainly due to radiation-induced damage to the bone marrow. This …

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Skin Lesion Prioritization: How AI Systems Fail When Tested Using Real-Scenario Databases

Iván Matas, Carmen Serrano, Lara Ferrándiz, Amalia Serrano et autres

The number of artificial intelligence (AI) systems developed for skin lesion classification has grown rapidly, notably driven by the release of publicly available datasets, such as those from the ISIC Archive. While this accessibility has allowed many research groups, often without a …

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Concordance in Basal Cell Carcinoma Diagnosis. Building a Proper Standard Reference to Train Artificial Intelligence Tools

Francisca Silva‐Clavería, Carmen Serrano, Iván Matas, Amalia Serrano et autres

BACKGROUND: Reliable labels are essential when training Artificial Intelligence (AI) tools. Whereas some diseases allow biopsy-based labeling, others rely on subjective criteria. For the diagnosis of basal cell carcinoma (BCC), dermatologists detect certain dermoscopic criteria, whose presence (or absence) serves as the …

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Advancing infantile hemangioma diagnosis by integrating temperature, color, and texture

J. A. Pérez‐Carrasco, Carmen Serrano, Juan Antonio Lenero-Bardallo, José Bernabéu‐Wittel et autres

Significance: Infantile hemangiomas are one of the most prevalent benign tumors in childhood. Typically, diagnosis relies on visual assessment of area, texture, and color. A few studies have focused on various color attributes in superficial and mixed Infantile hemangioma types, neglecting the …

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Domain-Specific Knowledge Distillation for Melanoma Depth in Dermatological Imaging

Miguel Nogales, Begoña Acha, Iván Matas, Carmen Serrano

Melanoma, a highly aggressive form of skin cancer, is primarily assessed by its depth of invasion (Breslow thickness), a key prognostic factor influencing clinical management. Deep learning has shown promising results in dermatological image analysis, yet its effectiveness is often hindered by …

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Mitigating Overfitting in Medical Imaging: Self-Supervised Pretraining vs. ImageNet Transfer Learning for Dermatological Diagnosis

Iván Matas, Carmen Serrano, Miguel Nogales, Lara Ferrándiz et autres

Deep learning has transformed computer vision but relies heavily on large labeled datasets and computational resources. Transfer learning, particularly fine-tuning pretrained models, offers a practical alternative; however, models pretrained on natural image datasets such as ImageNet may fail to capture domain-specific characteristics …

Discriminating BCC Subtypes Using Entropy and Mutual Information from Dermoscopic Features

Iván Matas, Begoña Acha, Francisca Silva‐Clavería, Amalia Serrano et autres

Objective: To analyze the frequency and co-occurrence of dermoscopic patterns in BCC lesions and their relationship with histopathologic subtypes, using statistical analysis and Information Theory tools such as entropy, conditional entropy, mutual information, and Hamming weight. Methods: A total of 223 dermoscopic …

El tratamiento de fisioterapia en el síndrome facetario lumbar. Una revisión bibliográfica

M. C. López Serrano, Raúl Morató Moscardó, Carmen Serrano, José De Andrés Ibáñez et autres

GASTROPARESIA PERSISTENTE Y SÍNDROME DE WERNICKE COMO COMPLICACIONES INFRECUENTES DEL BALÓN INTRAGÁSTRICO.

Jiacheng Cao, Belén Botella, Carmen Serrano, Paula Andrea Moreno Gutiérrez et autres

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

Francisca Silva‐Clavería, Carmen Serrano, Iván Matas, Amalia Serrano et autres

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 dermoscopic features. Objectives: To determine the consensus …

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

Miguel Nogales, Begoña Acha, Fernando Alarcón, José Pereyra et autres

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 invasion, …