The transparency of Artificial Intelligence (AI) models is an essential criterion for the deployment of AI in high-risk settings, such as medical applications. Consequently, numerous approaches for explaining AI systems have been proposed over the years (Samek et al., 2021).

In this blogpost we want to talk about color from a technical perspective. As you might already know, dermatologists use the ABCDE-criterium for the diagnosis of melanoma.

L’intelligence artificielle (l’IA) soulève aussi bien des questionnements philosophiques qu’informatiques, chacun a sa petite idée au sujet des IA. Mais qu’en savons-nous vraiment? 

The work "Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement", supported by iToBoS project, has been published.

In the iToBoS scanner, polarized light will be used to illuminate the skin of the patient. In this blogpost we want to explore what it means when we are talking about optical polarization.

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.