The scientific work "Explainable AI Methods - A Brief Overview", with the support of iToBoS project, has been published.
The scientific work "ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs", with the support of iToBoS project, has been published.
In iToBoS, machine learning/ artificial intelligence is key to combine all the design and make the system really a standout product.
Melanoma has a poor prognosis with median survival of 6-9 months in the absence of timely diagnosis and treatment.
Intégrer l’intelligence artificielle au domaine médical, c’est se poser les bonnes questions, notamment au niveau éthique.
On March 30th, scientists from the International Agency for Research on Cancer published a study on the Global Burden of Cutaneous Melanoma in 2020 and Projections to 2040.
iToBoS was presented in the framework of a course of the Academia Española de Dermatologia y Venereologia (AEDV) in Barcelona, Spain, on March 31, 2022.
iToBoS project has launched ai4pa (Artificial Intelligence For Patient Advocates) consisting in a training module oriented to patient advocates that serves as an introduction to transparent and explainable AI and its policy context.