3/03/2025.
The integration of digital technologies, e.g., smartphone apps, represents an impactful advancement in training for melanoma diagnosis.
3/03/2025.
The integration of digital technologies, e.g., smartphone apps, represents an impactful advancement in training for melanoma diagnosis.
26/02/2025.
The early detection and accurate monitoring of suspicious skin lesions are critical for effective dermatological diagnosis and treatment, particularly for reliable identification of the progression of nevi to melanoma.
24/02/2025.
This is the final blog in a three-part series explaining the technical reporting for explainable artificial intelligence (xAI) used in the iToBoS project.
20/02/2025.
This is the second blog in a series of three covering the iToBoS project’s approach to explainable artificial intelligence (xAI) technical reporting.
17/02/2025.
The University of Girona hosted the iToBoS Workshop on Skin Lesion Detection with 3D-TBP at the Politecnica-4 building, bringing together leading experts and practitioners in dermatology, medical imaging, machine learning, and artificial intelligence.
14/02/2025.
Don't miss the iToBoS Workshop on Skin Lesions Detection with 3D-TBP, which will take place at the University of Girona on February 17, 2025.
11/02/2025.
This is the first of three blogs covering explainable artificial intelligence (xAI) technical reporting in the iToBoS project.
5/02/2025.
The machine is formed by four robots, each of them moves the vision system device to the points defined by the Vision PC. Each robot will operate in a quadrant of the body map.
1/02/2025.
Melanoma is one of the most aggressive forms of skin cancer, responsible for 60% of lethal skin neoplasms. Early detection is crucial for improving patient outcomes, particularly as the incidence of melanoma continues to rise, posing an increasing public health challenge due to the aging population and extended life expectancy.
30/01/2025.
iToBoS partners held a joint workshop with the NEMECYS project to share information about project results (specifically the AI Privacy Risk Assessment tool) and gather feedback from relevant stakeholders from the health domain.