Explainable AI Methods - A Brief Overview


The scientific work "Explainable AI Methods - A Brief Overview", with the support of iToBoS project, has been published.

ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs


The scientific work "ECQx: Explainability-Driven Quantization for Low-Bit and Sparse DNNs", with the support of iToBoS project, has been published.

Overview of machine learning based approaches for non-contact dermoscopy


In iToBoS, machine learning/ artificial intelligence is key to combine all the design and make the system really a standout product.

The importance of Early Detection in the light of COVID-19


Melanoma has a poor prognosis with median survival of 6-9 months in the absence of timely diagnosis and treatment.

[FR] Quelle éthique pour l’intelligence artificielle en santé ?


Intégrer l’intelligence artificielle au domaine médical, c’est se poser les bonnes questions, notamment au niveau éthique. 

iToBoS 2nd Newsletter launched


The second issue of the iToBoS newsletter was released!!

Why the early detection of Melanoma will become more important than ever


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.

Outstanding impact of iToBoS project in the media


iToBoS project aims to provide new opportunities and added value to society in terms of novel health solutions, patient care, innovation, technical improvements and economic development.

iToBoS presented in a course of the Spanish Academy of Dermatology and Venereology


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’s ai4pa, Artificial Intelligence for Patient Advocates online course


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.