[FR] L'intelligence artificielle, qu'est-ce que c'est?

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? 

Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement

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

What is polarized light?

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, AI detection of melanoma and 100+ other types of skin tumors 

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.

Digital trends in the health sector

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.

Sunburn explainer

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?

Measurably Stronger Explanation Reliability via Model Canonization

The work "Measurably Stronger Explanation Reliability via Model Canonization", supported by iToBoS project, has been published.

Structured data classification

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.

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations

The work "Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations", supported by iToBoS project, has been published.

PatClarC: Using pattern concept activation vectors for noise-robust model debugging

The scientific work "PatClarC: Using pattern concept activation vectors for noise-robust model debugging", with the support of iToBoS project, has been published.