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1. BCN20000: Dermoscopic Lesions in the Wild

Author

Hernández-Pérez, Carlos, Combalia, Marc, Podlipnik, Sebastian, Codella, Noel C. F., Rotemberg, Veronica, Halpern, Allan C., Reiter, Ofer, Carrera, Cristina, Barreiro, Alicia, Helba, Brian, Puig, Susana, Vilaplana, Veronica, and Malvehy, Josep

Published
2024
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2. Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Author

Chanda, Tirtha, Hauser, Katja, Hobelsberger, Sarah, Bucher, Tabea-Clara, Garcia, Carina Nogueira, Wies, Christoph, Kittler, Harald, Tschandl, Philipp, Navarrete-Dechent, Cristian, Podlipnik, Sebastian, Chousakos, Emmanouil, Crnaric, Iva, Majstorovic, Jovana, Alhajwan, Linda, Foreman, Tanya, Peternel, Sandra, Sarap, Sergei, Özdemir, İrem, Barnhill, Raymond L., Llamas-Velasco, Mar, Poch, Gabriela, Korsing, Sören, Sondermann, Wiebke, Gellrich, Frank Friedrich, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Goebeler, Matthias, Schilling, Bastian, Utikal, Jochen S., Ghoreschi, Kamran, Fröhling, Stefan, Krieghoff-Henning, Eva, and Brinker, Titus J.

Published
2024
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3. Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Author

Chanda, Tirtha, Hauser, Katja, Hobelsberger, Sarah, Bucher, Tabea-Clara, Garcia, Carina Nogueira, Wies, Christoph, Kittler, Harald, Tschandl, Philipp, Navarrete-Dechent, Cristian, Podlipnik, Sebastian, Chousakos, Emmanouil, Crnaric, Iva, Majstorovic, Jovana, Alhajwan, Linda, Foreman, Tanya, Peternel, Sandra, Sarap, Sergei, Özdemir, İrem, Barnhill, Raymond L., Velasco, Mar Llamas, Poch, Gabriela, Korsing, Sören, Sondermann, Wiebke, Gellrich, Frank Friedrich, Heppt, Markus V., Erdmann, Michael, Haferkamp, Sebastian, Drexler, Konstantin, Goebeler, Matthias, Schilling, Bastian, Utikal, Jochen S., Ghoreschi, Kamran, Fröhling, Stefan, Krieghoff-Henning, Eva, and Brinker, Titus J.

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Although artificial intelligence (AI) systems have been shown to improve the accuracy of initial melanoma diagnosis, the lack of transparency in how these systems identify melanoma poses severe obstacles to user acceptance. Explainable artificial intelligence (XAI) methods can help to increase transparency, but most XAI methods are unable to produce precisely located domain-specific explanations, making the explanations difficult to interpret. Moreover, the impact of XAI methods on dermatologists has not yet been evaluated. Extending on two existing classifiers, we developed an XAI system that produces text and region based explanations that are easily interpretable by dermatologists alongside its differential diagnoses of melanomas and nevi. To evaluate this system, we conducted a three-part reader study to assess its impact on clinicians' diagnostic accuracy, confidence, and trust in the XAI-support. We showed that our XAI's explanations were highly aligned with clinicians' explanations and that both the clinicians' trust in the support system and their confidence in their diagnoses were significantly increased when using our XAI compared to using a conventional AI system. The clinicians' diagnostic accuracy was numerically, albeit not significantly, increased. This work demonstrates that clinicians are willing to adopt such an XAI system, motivating their future use in the clinic.

Published
2023
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5. Prognostic factors for satellitosis or in-transit metastasis in cutaneous squamous cell carcinoma: A multicentric cohort study

Author

Marti-Marti, Ignasi, Podlipnik, Sebastian, Cañueto, Javier, Ferrándiz-Pulido, Carla, Deza, Gustavo, Sanmartín, Onofre, Jaka, Ane, Beà-Ardèbol, Sonia, Botella-Estrada, Rafael, Redondo, Pedro, Turrión-Merino, Lucía, Ruiz-Salas, Verónica, Masferrer, Emili, Yébenes, Mireia, Sánchez-Schmidt, Júlia-María, Gracia-Darder, Inés, Altemir-Vidal, Arcadi, Aguayo-Ortiz, Rafael S., Becerril, Sara, Bodet-Castillo, Domingo, Leal, Lorena, Fuente, Maria José, Moreno-Arrones, Oscar Muñoz, Abril-Pérez, Carlos, Tomás-Velázquez, Alejandra, Sandoval-Clavijo, Alejandra, and Toll, Agustí

Published
2023
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8. Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge

Author

Combalia, Marc, Codella, Noel, Rotemberg, Veronica, Carrera, Cristina, Dusza, Stephen, Gutman, David, Helba, Brian, Kittler, Harald, Kurtansky, Nicholas R, Liopyris, Konstantinos, Marchetti, Michael A, Podlipnik, Sebastian, Puig, Susana, Rinner, Christoph, Tschandl, Philipp, Weber, Jochen, Halpern, Allan, and Malvehy, Josep

Published
2022
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9. PRRX1 silencing is required for metastatic outgrowth in melanoma and is an independent prognostic of reduced survival in patients.

Author

Ferreres, Josep R., Vinyals, Antònia, Campos‐Martin, Rafael, Espín, Roderic, Podlipnik, Sebastian, Ramos, Raquel, Bertran, Esther, Carrera, Cristina, Marcoval, Joaquim, Malvehy, Josep, Fabregat, Isabel, Puig, Susana, and Fabra, Àngels

Abstract

Paired related homeobox 1 (PRRX1) is an inducer of epithelial‐to‐mesenchymal transition (EMT) in different types of cancer cells. We detected low PRRX1 expression in nevus but increased levels in primary human melanoma and cell lines carrying the BRAFV600E mutation. High expression of PRRX1 correlates with invasiveness and enrichment of genes belonging to the EMT programme. Conversely, we found that loss of PRRX1 in metastatic samples is an independent prognostic predictor of poor survival for melanoma patients. Here, we show that stable depletion of PRRX1 improves the growth of melanoma xenografts and increases the number of distant spontaneous metastases, compared to controls. We provide evidence that loss of PRRX1 counteracts the EMT phenotype, impairing the expression of other EMT‐related transcription factors, causing dysregulation of the ERK and signal transducer and activator of transcription 3 (STAT3) signaling pathways, and abrogating the invasive and migratory properties of melanoma cells while triggering the up‐regulation of proliferative/melanocytic genes and the expression of the neural‐crest‐like markers nerve growth factor receptor (NGFR; also known as neurotrophin receptor p75NTR) and neural cell adhesion molecule L1 (L1CAM). Overall, our results indicate that loss of PRRX1 triggers a switch in the invasive programme, and cells de‐differentiate towards a neural crest stem cell (NCSC)‐like phenotype that accounts for the metastatic aggressiveness. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts

Author

Haggenmüller, Sarah, Maron, Roman C., Hekler, Achim, Utikal, Jochen S., Barata, Catarina, Barnhill, Raymond L., Beltraminelli, Helmut, Berking, Carola, Betz-Stablein, Brigid, Blum, Andreas, Braun, Stephan A., Carr, Richard, Combalia, Marc, Fernandez-Figueras, Maria-Teresa, Ferrara, Gerardo, Fraitag, Sylvie, French, Lars E., Gellrich, Frank F., Ghoreschi, Kamran, Goebeler, Matthias, Guitera, Pascale, Haenssle, Holger A., Haferkamp, Sebastian, Heinzerling, Lucie, Heppt, Markus V., Hilke, Franz J., Hobelsberger, Sarah, Krahl, Dieter, Kutzner, Heinz, Lallas, Aimilios, Liopyris, Konstantinos, Llamas-Velasco, Mar, Malvehy, Josep, Meier, Friedegund, Müller, Cornelia S.L., Navarini, Alexander A., Navarrete-Dechent, Cristián, Perasole, Antonio, Poch, Gabriela, Podlipnik, Sebastian, Requena, Luis, Rotemberg, Veronica M., Saggini, Andrea, Sangueza, Omar P., Santonja, Carlos, Schadendorf, Dirk, Schilling, Bastian, Schlaak, Max, Schlager, Justin G., Sergon, Mildred, Sondermann, Wiebke, Soyer, H. Peter, Starz, Hans, Stolz, Wilhelm, Vale, Esmeralda, Weyers, Wolfgang, Zink, Alexander, Krieghoff-Henning, Eva, Kather, Jakob N., von Kalle, Christof, Lipka, Daniel B., Fröhling, Stefan, Hauschild, Axel, Kittler, Harald, and Brinker, Titus J.

Published
2021
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13. Differences in cutaneous melanoma survival between the 7th and 8th edition of the American Joint Committee on Cancer (AJCC). A multicentric population-based study

Author

Barreiro-Capurro, Alicia, Andrés-Lencina, Juan J., Podlipnik, Sebastian, Carrera, Cristina, Requena, Celia, Manrique-Silva, Esperanza, Quaglino, Pietro, Tonella, Luca, Jaka, Ane, Richarz, Nina, Rodríguez-Peralto, José L., Ortiz, Pablo, Boada, Aram, Ribero, Simone, Nagore, Eduardo, Malvehy, Josep, and Puig, Susana

Published
2021
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14. BCN20000: dermoscopic lesions in the wild

Author

Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group, Hernández Pérez, Carlos, Combalia Escudero, Marc, Podlipnik, Sebastian, Codella, Noel C. F., Rotemberg, Veronica, Halpern, Allan C., Reiter, Ofer, Carrera Álvarez, Cristina, Barreiro Capurro, Alicia, Helba, Brian, Puig Sardá, Susana, Vilaplana Besler, Verónica, Malvehy Guilera, Josep, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group, Hernández Pérez, Carlos, Combalia Escudero, Marc, Podlipnik, Sebastian, Codella, Noel C. F., Rotemberg, Veronica, Halpern, Allan C., Reiter, Ofer, Carrera Álvarez, Cristina, Barreiro Capurro, Alicia, Helba, Brian, Puig Sardá, Susana, Vilaplana Besler, Verónica, and Malvehy Guilera, Josep

Abstract

Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning from 2010 to 2016, collated at the Hospital Clínic in Barcelona, Spain. The BCN20000 dataset aims to address the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions in hard-to-diagnose locations such as those found in nails and mucosa, large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. Our dataset covers eight key diagnostic categories in dermoscopy, providing a diverse range of lesions for artificial intelligence model training. Furthermore, a ninth out-of-distribution (OOD) class is also present on the test set, comprised of lesions which could not be distinctively classified as any of the others. By providing a comprehensive collection of varied images, BCN20000 helps bridge the gap between the training data for machine learning models and the day-to-day practice of medical practitioners. Additionally, we present a set of baseline classifiers based on state-of-the-art neural networks, which can be extended by other researchers for further experimentation., We acknowledge the support of the International Skin Imaging Collaboration (ISIC). This research was supported by the Spanish Research Agency (AEI) under project PID2020-116907RB-I00 of the call MCIN/ AEI /10.13039/501100011033 and the project 718/C/2019 with id 201923-30 and 201923-31, funded by Fundació la Marató de TV3, iTOBOs grant from the European Union’s Horizon 2020 research and innovation programme num 965221. Other funding sources include the Melanoma Research Alliance Young Investigator Award 614197. This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748., Peer Reviewed, Postprint (published version)

Published
2024

15. Position statement of the EADV Artificial Intelligence (AI) Task Force on AI‐assisted smartphone apps and web‐based services for skin disease

Author

Sangers, Tobias E; https://orcid.org/0000-0003-0948-5801, Kittler, Harald; https://orcid.org/0000-0002-0051-8016, Blum, Andreas, Braun, Ralph P; https://orcid.org/0000-0003-1253-8206, Barata, Catarina, Cartocci, Alessandra; https://orcid.org/0000-0002-1818-6275, Combalia, Marc; https://orcid.org/0000-0001-5237-4256, Esdaile, Ben, Guitera, Pascale; https://orcid.org/0000-0001-9519-110X, Haenssle, Holger A; https://orcid.org/0000-0001-7255-3104, Kvorning, Niels; https://orcid.org/0000-0002-8034-6727, Lallas, Aimilios; https://orcid.org/0000-0002-7193-0964, Navarrete‐Dechent, Cristian; https://orcid.org/0000-0003-4040-3640, Navarini, Alexander A; https://orcid.org/0000-0001-7059-632X, Podlipnik, Sebastian; https://orcid.org/0000-0003-4150-0522, Rotemberg, Veronica, Soyer, H Peter; https://orcid.org/0000-0002-4770-561X, Tognetti, Linda; https://orcid.org/0000-0002-6691-4310, Tschandl, Philipp; https://orcid.org/0000-0003-0391-7810, Malvehy, Josep; https://orcid.org/0000-0002-6998-914X, Sangers, Tobias E; https://orcid.org/0000-0003-0948-5801, Kittler, Harald; https://orcid.org/0000-0002-0051-8016, Blum, Andreas, Braun, Ralph P; https://orcid.org/0000-0003-1253-8206, Barata, Catarina, Cartocci, Alessandra; https://orcid.org/0000-0002-1818-6275, Combalia, Marc; https://orcid.org/0000-0001-5237-4256, Esdaile, Ben, Guitera, Pascale; https://orcid.org/0000-0001-9519-110X, Haenssle, Holger A; https://orcid.org/0000-0001-7255-3104, Kvorning, Niels; https://orcid.org/0000-0002-8034-6727, Lallas, Aimilios; https://orcid.org/0000-0002-7193-0964, Navarrete‐Dechent, Cristian; https://orcid.org/0000-0003-4040-3640, Navarini, Alexander A; https://orcid.org/0000-0001-7059-632X, Podlipnik, Sebastian; https://orcid.org/0000-0003-4150-0522, Rotemberg, Veronica, Soyer, H Peter; https://orcid.org/0000-0002-4770-561X, Tognetti, Linda; https://orcid.org/0000-0002-6691-4310, Tschandl, Philipp; https://orcid.org/0000-0003-0391-7810, and Malvehy, Josep; https://orcid.org/0000-0002-6998-914X

Abstract

Background: As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer. Objective: This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI‐assisted smartphone applications (apps) and web‐based services for skin diseases with emphasis on skin cancer detection.MethodsAn initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance. Results: Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non‐medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web‐based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users. Conclusions: The utilisation of AI‐assisted smartphone apps and web‐based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of th

Published
2024

17. Restrospective reappraisal of the prognostic classification of spitzoid melanocytic neoplasms after BRAF and NRAS mutation characterisation: a single institution experience

Author

Moysset, Irene, primary, Castrejon, Natalia, additional, Garcia‐Herrera, Adriana, additional, Castillo, Paola, additional, Marginet, Marta, additional, Teixido, Cristina, additional, Podlipnik, Sebastian, additional, Albero‐Gonzalez, Raquel, additional, Montironi, Carla, additional, Navarro, Judit, additional, Rovira, Carlota, additional, Puig, Susana, additional, Carrera, Cristina, additional, and Alos, Llucia, additional

Published
2024
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20. Predictive and Prognostic Factors in Melanoma Central Nervous System Metastases—A Cohort Study.

Author

Serra, Estefania, Abarzua-Araya, Álvaro, Arance, Ana, Martin-Huertas, Roberto, Aya, Francisco, Olondo, María Lourdes, Rizo-Potau, Daniel, Malvehy, Josep, Puig, Susana, Carrera, Cristina, and Podlipnik, Sebastian

Subjects
BRAIN tumor risk factors, RISK assessment, CANCER treatment, PREDICTION models, RESEARCH funding, CANCER invasiveness, MULTIPLE regression analysis, TUMOR markers, DESCRIPTIVE statistics, AGE distribution, LACTATE dehydrogenase, MENINGEAL cancer, CANCER patients, METASTASIS, LONGITUDINAL method, KAPLAN-Meier estimator, SURVIVAL analysis (Biometry), TORSO, CUTANEOUS malignant melanoma, BRAIN tumors, SPECIALTY hospitals, REGRESSION analysis, PROPORTIONAL hazards models, SKIN ulcers, DISEASE risk factors, DISEASE complications
Abstract

Simple Summary: We conducted a study at the Melanoma Unit of the Hospital Clinic of Barcelona to investigate brain metastases in patients with cutaneous melanoma. We collected data from patients diagnosed between January 1998 and September 2023. Patients with melanoma in situ or those with prior lung or breast cancer were excluded. Our aim was to identify factors associated with the development and survival outcomes of brain metastases. We analyzed patient demographics, tumor characteristics, and survival data. The diagnosis of brain metastases was confirmed using imaging techniques, and biopsies were performed when feasible. Our study followed strict guidelines for reporting observational studies. We found that younger age and larger primary tumor thickness increased the risk of developing brain metastases. Additionally, the presence of ulceration and microscopic satellitosis in the primary tumor were associated with a higher risk. Melanomas located on the trunk had a higher risk compared to those on the extremities. Patients with brain metastases had a median survival of around six months. Neurological symptoms and leptomeningeal involvement were associated with poorer survival outcomes. Higher number of brain lesions and elevated levels of lactate dehydrogenase (LDH) also predicted worse survival. Our findings highlight the importance of early detection and monitoring of melanoma patients, especially those at higher risk of brain metastases. Understanding these factors can aid in personalized treatment approaches and improving patient outcomes. Background: Melanoma is the cancer with the highest risk of dissemination to the central nervous system (CNS), one of the leading causes of mortality from this cancer. Objective: To identify patients at higher risk of developing CNS metastases and to evaluate associated prognostic factors. Methods: A cohort study (1998–2023) assessed patients who developed CNS melanoma metastases. Multivariate logistic regression was used to identify predictive factors at melanoma diagnosis for CNS metastasis. Cox regression analysis evaluated the CNS-independent metastasis-related variables impacting survival. Results: Out of 4718 patients, 380 (8.05%) developed CNS metastases. Multivariate logistic regression showed that a higher Breslow index, mitotic rate ≥ 1 mm2, ulceration, and microscopic satellitosis were significant risk factors for CNS metastasis development. Higher patient age and the location of the primary tumor in the upper or lower extremities were protective factors. In survival analysis, post-CNS metastasis, symptomatic disease, prior non-CNS metastases, CNS debut with multiple metastases, elevated LDH levels, and leptomeningeal involvement correlated with poorer survival. Conclusion: Predictive factors in the primary tumor independently associated with brain metastases include microscopic satellitosis, ulceration, higher Breslow index, and trunk location. Prognostic factors for lower survival in CNS disease include symptomatic disease, multiple CNS metastases, and previous metastases from different sites. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Validation of epidermal AMBRA1 and loricrin (AMBLor) as a prognostic biomarker for nonulcerated American Joint Committee on Cancer stage I/II cutaneous melanoma

Author

Ewen, Tom, primary, Husain, Akhtar, additional, Stefanos, Niki, additional, Barrett, Paul, additional, Jones, Claire, additional, Ness, Tom, additional, Long, Anna, additional, Horswell, Stuart, additional, Bosomworth, Helen, additional, Lowenstein, Joe, additional, Richardson, Grant, additional, Swan, David, additional, McConnell, Ashleigh, additional, Rose, Aidan, additional, Andrew, Tom, additional, Reynolds, Nick, additional, Malvehy, Josep, additional, Carrera, Christina, additional, Alos, Llucia, additional, Mailer, Sonia, additional, Helm, Thomas, additional, Ding, Liang, additional, Bogner, Paul, additional, Podlipnik, Sebastian, additional, Puig, Susana, additional, McArthur, Grant A, additional, Paragh, Gyorgy, additional, Labus, Marie, additional, Sloan, Philip, additional, Armstrong, Jane L, additional, and Lovat, Penny E, additional

Published
2023
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22. Topographical and Chronological Analysis of Thin Cutaneous Melanoma’s Progressions: A Multicentric Study

Author

Chousakos, Emmanouil, primary, Zugna, Daniela, additional, Dika, Emi, additional, Boada, Aram, additional, Podlipnik, Sebastian, additional, Carrera, Cristina, additional, Malvehy, Josep, additional, Puig, Susana, additional, Requena, Celia, additional, Manrique-Silva, Esperanza, additional, Nagore, Eduardo, additional, Quaglino, Pietro, additional, Senetta, Rebecca, additional, and Ribero, Simone, additional

Published
2023
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23. Spaghetti Technique Versus Wide Local Excision for Lentigo Maligna Affecting the Head and Neck Regions: Surgical Outcome and Descriptive Analysis of 79 Cases From a Single Practice Cohort

Author

Martinez-Molina, Manel, primary, Richarz, Nina, additional, Jaka, Ane, additional, Bassas-Vila, Juli, additional, Mora-Fernández, Verónica, additional, Quer Pi-Sunyer, Ariadna, additional, Podlipnik, Sebastian, additional, Carrascosa, José Manuel, additional, and Boada, Aram, additional

Published
2023
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24. Position statement of the EADV Artificial Intelligence (AI) Task Force on AI‐assisted smartphone apps and web‐based services for skin disease.

Author

Sangers, Tobias E., Kittler, Harald, Blum, Andreas, Braun, Ralph P., Barata, Catarina, Cartocci, Alessandra, Combalia, Marc, Esdaile, Ben, Guitera, Pascale, Haenssle, Holger A., Kvorning, Niels, Lallas, Aimilios, Navarrete‐Dechent, Cristian, Navarini, Alexander A., Podlipnik, Sebastian, Rotemberg, Veronica, Soyer, H. Peter, Tognetti, Linda, Tschandl, Philipp, and Malvehy, Josep

Subjects
ARTIFICIAL intelligence, MOBILE apps, SKIN diseases, TASK forces, LITERATURE reviews, DERMATOLOGISTS
Abstract

Background: As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer. Objective: This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI‐assisted smartphone applications (apps) and web‐based services for skin diseases with emphasis on skin cancer detection. Methods: An initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance. Results: Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non‐medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web‐based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users. Conclusions: The utilisation of AI‐assisted smartphone apps and web‐based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of these apps into clinical practice. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Melanoma-specific survival is worse in the elderly: a multicentric cohort study.

Author

Segura, Sonia, Podlipnik, Sebastian, Boada, Aram, Martí, Rosa M., Sabat, Mireia, Yélamos, Oriol, Zarzoso-Muñoz, Inés, Azón-Masoliver, Antoni, López-Castillo, Daniel, Solà, Joaquim, Baliu-Piqué, Carola, Galvany-Rossell, Loida, Pasquali, Paola, Just-Sarobé, Miquel, Duran, Xavier, Carrera, Cristina, Richarz, Nina A., Pujol, Ramon M., Malvehy, Josep, and Puig, Susana

Published
2023
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28. Prognostic factors of satellitosis or in-transit metastasis in cutaneous squamous cell carcinoma. A multicentric cohort study

Author

Marti-Marti, Ignasi, primary, Podlipnik, Sebastian, additional, Cañueto, Javier, additional, Ferrándiz-Pulido, Carla, additional, Deza, Gustavo, additional, Sanmartín, Onofre, additional, Jaka, Ane, additional, Beà-Ardèbol, Sonia, additional, Botella-Estrada, Rafael, additional, Redondo, Pedro, additional, Turrión-Merino, Lucía, additional, Ruiz-Salas, Verónica, additional, Masferrer, Emili, additional, Yébenes, Mireia, additional, Sánchez-Schmidt, Júlia-María, additional, Gracia-Darder, Inés, additional, Altemir-Vidal, Arcadi, additional, Aguayo-Ortiz, Rafael S, additional, Becerril, Sara, additional, Bodet-Castillo, Domingo, additional, Leal, Lorena, additional, Fuente, Maria José, additional, Moreno-Arrones, Oscar Muñoz, additional, Abril-Pérez, Carlos, additional, Tomás-Velázquez, Alejandra, additional, Sandoval-Clavijo, Alejandra, additional, and Toll, Agustí, additional

Published
2023
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29. Analysis of dermoscopic changes of blue nevi on digital follow‐up: a 21‐year retrospective cohort study

Author

Alamon‐Reig, Francesc, primary, Combalia, Marc, additional, Albero‐González, Raquel, additional, Alòs, Llúcia, additional, Carrera, Cristina, additional, Puig‐Butillé, Joan Anton, additional, Villanueva‐Cañas, José Luis, additional, Puig, Susana, additional, Malvehy, Josep, additional, and Podlipnik, Sebastian, additional

Published
2023
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30. Real-World Experience with Vismodegib on Advanced and Multiple BCCs: Data from the RELIVIS Study

Author

Ruiz-Salas, Verónica, primary, Podlipnik, Sebastian, additional, Sandoval-Clavijo, Alejandra, additional, Sanmartin-Jiménez, Onofre, additional, Bernia-Petit, Eduardo, additional, Bonfill-Ortí, Montserrat, additional, Bassas-Freixas, Patricia, additional, Yebenes-Marsal, Mireia, additional, Flórez-Menéndez, Ángeles, additional, Solá-Ortigosa, Joaquim, additional, Just-Sarobé, Miquel, additional, Aguayo-Ortiz, Rafael, additional, Masferrer i Niubó, Emili, additional, Quintana-Codina, Mónica, additional, Deza, Gustavo, additional, Jaka, Ane, additional, Fuentes, Maria José, additional, Cañueto, Javier, additional, and Toll, Agustí, additional

Published
2023
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32. Clinical associations and classification of immune checkpoint inhibitor-induced cutaneous toxicities: a multicentre study from the European Academy of Dermatology and Venereology Task Force of Dermatology for Cancer Patients

Author

Nikolaou, Vasiliki A., primary, Apalla, Zoe, additional, Carrera, Cristina, additional, Fattore, Davide, additional, Sollena, Pietro, additional, Riganti, Julia, additional, Segura, Sonia, additional, Freites-Martinez, Azael, additional, Lallas, Konstantinos, additional, Romano, Maria Concetta, additional, Oikonomou, Chrysa, additional, Starace, Michela, additional, Dimopoulos, Meletios A., additional, Kyrgidis, Athanassios, additional, Lazaridou, Elizabeth, additional, Giavedoni, Priscila, additional, Annunziata, Maria Carmela, additional, Peris, Ketty, additional, Echeverría, Maria, additional, Lopez-Tujillo, Emilio, additional, Syrigos, Konstandinos, additional, Papageorgiou, Chryssoula, additional, Podlipnik, Sebastian, additional, Fabbrocini, Gabriella, additional, Torre, Ana C., additional, Kemanetzi, Christina, additional, Villa-Crespo, Lorena, additional, Lallas, Aimilios, additional, Stratigos, Alexander J., additional, and Sibaud, Vincent, additional

Published
2022
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33. Common genetic variants associated with melanoma risk or naevus count in patients with wildtype MC1R melanoma

Author

Calbet-Llopart, Neus, primary, Combalia, Marc, additional, Kiroglu, Anil, additional, Potrony, Miriam, additional, Tell-Martí, Gemma, additional, Combalia, Andrea, additional, Brugues, Albert, additional, Podlipnik, Sebastian, additional, Carrera, Cristina, additional, Puig, Susana, additional, Malvehy, Josep, additional, and Puig-Butillé, Joan Anton, additional

Published
2022
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43. Timeline of Adverse Events during Immune Checkpoint Inhibitors for Advanced Melanoma and Their Impacts on Survival

Author

Villa-Crespo, Lorena, primary, Podlipnik, Sebastian, additional, Anglada, Natalia, additional, Izquierdo, Clara, additional, Giavedoni, Priscila, additional, Iglesias, Pablo, additional, Dominguez, Mireia, additional, Aya, Francisco, additional, Arance, Ana, additional, Malvehy, Josep, additional, Puig, Susana, additional, and Carrera, Cristina, additional

Published
2022
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44. Using a 31-Gene Expression Profile Test to Stratify Patients with Stage I–II Cutaneous Melanoma According to Recurrence Risk: Update to a Prospective, Multicenter Study

Author

Podlipnik, Sebastian, primary, Boada, Aram, additional, López-Estebaranz, Jose L., additional, Martín-González, Manuel M., additional, Redondo, Pedro, additional, Martin, Brian, additional, Quick, Ann P., additional, Bailey, Christine N., additional, Kurley, Sarah J., additional, Cook, Robert W., additional, and Puig, Susana, additional

Published
2022
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46. Sentinel Lymph Node Biopsy vs. Observation in Thin Melanoma: A Multicenter Propensity Score Matching Study

Author

Tejera-Vaquerizo, Antonio, primary, Boada, Aram, additional, Ribero, Simone, additional, Puig, Susana, additional, Paradela, Sabela, additional, Moreno-Ramírez, David, additional, Cañueto, Javier, additional, de Unamuno-Bustos, Blanca, additional, Brinca, Ana, additional, Descalzo-Gallego, Miguel A., additional, Osella-Abate, Simona, additional, Cassoni, Paola, additional, Podlipnik, Sebastian, additional, Carrera, Cristina, additional, Vidal-Sicart, Sergi, additional, Pigem, Ramón, additional, Toll, Agustí, additional, Rull, Ramón, additional, Alos, Llucìa, additional, Requena, Celia, additional, Bolumar, Isidro, additional, Traves, Víctor, additional, Pla, Ángel, additional, Fernández-Orland, Almudena, additional, Jaka, Ane, additional, Fernández-Figueras, María Teresa, additional, Richarz, Nina Anika, additional, Vieira, Ricardo, additional, Botella-Estrada, Rafael, additional, Román-Curto, Concepción, additional, Ferrándiz-Pulido, Lara, additional, Iglesias-Pena, Nicolás, additional, Ferrándiz, Carlos, additional, Malvehy, Josep, additional, Quaglino, Pietro, additional, and Nagore, Eduardo, additional

Published
2021
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