The challenges of infusing privacy and compliance technologies in the iToBoS project


In any data processing project that deals with personal information there is an inherent tradeoff between safeguarding data subjects’ privacy and yielding useful and accurate insights from the data.

iToBoS project presented in Green Project Expo


The iToBoS project, its challenges and it purposes have been presented in the Green Project Expo.

Classification system for skin lesions, the more detailed the better


Skin cancer is one of the most common cancers in the world. Late-stage skin cancers spreads to internal organs and become fatal. Early-stage skin cancer can be cured with a high survival rate, while the 5-year survival rate for skin cancer is extremely low. 

[GR] iToBoS – Ευφυής Σαρωτής Ολόκληρου του Δώματος για την Έγκαιρη Διάγνωση Μελανώματος


Το iToBoS είναι ένα ερευνητικό έργο που χρηματοδοτείται από το πρόγραμμα έρευνας και καινοτομίας της Ευρωπαϊκής Επιτροπής Horizon 2020, στο θέμα "Ψηφιακή διαγνωστική - Ανάπτυξη εργαλείων για την υποστήριξη κλινικών αποφάσεων ενσωματώνοντας διάφορα είδη διαγνωστικών δεδομένων".

Skin Cancers: Data and facts


The most updated source for worldwide cancer data is represented by the GLOBOCAN 2020 report of the International Agency of Cancer Research (IACR).

Understanding DICOM


DICOM stands for Digital Imaging and COmmunications in Medicine: it is an international standard related to the exchange, storage and communication of digital medical images and other related digital data.

The value of clinical data


Over the last half century, clinicians and researchers have made enormous advances in detecting and treating melanoma.

Uncertainty Estimation in Deep Neural Networksfor Dermoscopic Image Classification


Machine learning and specifically deep learning, have dramatically improved the state-of-the-art in many areas of research, including computer vision, speech recognition, and natural language processing.

Explain and improve: LRP-inference fine-tuning for image captioning models


The work “Explain and improve: LRP-inference fine-tuning for image captioning models”, with the support of iToBoS project, has been published in ScienceDirect.

Ethical Workshop


iToBoS organized the workshop entitled “Ethical impact of the use of AI technologies for the detection of melanoma as addressed in iToBoS”.