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Project

SkinCare (EIT)

SkinCare

SkinCare

  • Duration:

The EIT digital project SkinCare is developing a mobile app for patients in the context of skin cancer diagnosis and treatment. The combination of patient data and image data enables decision support and services in clinical as well as non-clinical contexts.

Sponsors

EU - European Union

H2020 EIT-Digital19232

EU - European Union

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Contact Person
Prof. Dr.-Ing. Daniel Sonntag
Prof. Dr.-Ing. Daniel Sonntag

Keyfacts

Publications about the project

On the Overlap Between Grad-CAM Saliency Maps and Explainable Visual Features in Skin Cancer Images

Fabrizio Nunnari; Md Abdul Kadir; Daniel Sonntag

In: Andreas Holzinger; Peter Kieseberg; A. Min Tjoa; Edgar Weippl (Hrsg.). Machine Learning and Knowledge Extraction. International IFIP Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE) (CD-MAKE-2021), August 17-20, Virtual, Pages 241-253, LNCS, Vol. 12844, ISBN 978-3-030-84060-0, Springer International Publishing, 2021.

To the publication

Anomaly Detection for Skin Lesion Images Using Replicator Neural Networks

Fabrizio Nunnari; Hasan Md Tusfiqur Alam; Daniel Sonntag

In: Andreas Holzinger; Peter Kieseberg; A. Min Tjoa; Edgar Weippl (Hrsg.). Machine Learning and Knowledge Extraction. International IFIP Cross Domain (CD) Conference for Machine Learning & Knowledge Extraction (MAKE) (CD-MAKE-2021), August 17-20, Virtual, Pages 225-240, LNCS, Vol. 12844, ISBN 978-3-030-84060-0, Springer International Publishing, 2021.

To the publication

The effects of masking in melanoma image classification with CNNs towards international standards for image preprocessing

Fabrizio Nunnari; Abraham Ezema; Daniel Sonntag

In: 2020 EAI International Symposium on Medical Artificial Intelligence. EAI International Symposium on Medical Artificial Intelligence (MedAI-2020), December 18, Online-Conference, EAI, 12/2020.

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All publications