10/03/2022.
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.
9/03/2022.
The iToBoS 2nd Project Management Board (PMB) meeting took place on 9/03/2022 throughout video conference system with the attendance of 17 attendees, including the Project Coordinator (PC), Project Manager (PM), Innovation and Exploitation Manager (IEM), Dissemination and Communication Manager (DCM), Data Manager (DM), Quality Assurance Manager (QAM) and WP leaders.
5/03/2022.
iToBoS presents the objectives, challenges and expected benefits of the project at the MWC Open Innovation Challenge 2022 among a wide and multidisciplinary audience.
4/03/2022.
iToBoS project was presented in the 4 Years From Now (4YFN) congress, held in Barcelona from February 28 to March 3, 2022.
28/02/2022.
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?
27/02/2022
The work "Measurably Stronger Explanation Reliability via Model Canonization", supported by iToBoS project, has been published.
24/02/2022.
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.
22/02/2022.
The work "Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations", supported by iToBoS project, has been published.
18/02/2022.
The scientific paper "PatClarC: Using pattern concept activation vectors for noise-robust model debugging", with the support of the iToBoS project, was published.
16/02/2022.
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.