Skin cancer is one of the most common cancers in the world. In the US alone, between 3 to 5 million new cases are reported each year, with treatment costs of approximately $9 billion.
iToBoS members attended the Mobile World Congress not only to present the project proposal and receive feedback from the ecosystem, but also to discover and learn more about the latest trends in IT solutions applied to personalized medicine.
You’ve probably heard it said that the main cause of melanomas is too much sun exposure and many of us are familiar with the painful red skin, blisters and peeling that follow too much time in the sun. But what actually happens in the skin during a sunburn?
The work "Measurably Stronger Explanation Reliability via Model Canonization", supported by iToBoS project, has been published.
Data classification is the process of classifying data as a whole (e.g. database schema) or its parts (e.g. column name, column values) into categories. It can also be evaluated for its identifiability, sensitivity and/or confidentiality. In this work, our focus lies in and around structured (and semi structured) data.
The work "Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations", supported by iToBoS project, has been published.
The scientific work "PatClarC: Using pattern concept activation vectors for noise-robust model debugging", with the support of iToBoS project, has been published.
In the iToBoS project, the so-called 3D cameras are used. These cameras enable us to make a virtual representation of the patient. This can help the dermatologists to match dermoscopic images of lesions with the lesions on the body of the patient.
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. Therefore, early detection is the key in fighting skin cancer.
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".