xAI Technical Reporting – Part One

11/02/2025.

This is the first of three blogs covering explainable artificial intelligence (xAI) technical reporting in the iToBoS project.

The complete assembly of the final scanner

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.

Standards in whole body photography, digital dermoscopy and artificial intelligence applied to the early diagnosis of melanoma

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.

Joint workshop of the stakeholders of the NEMECYS and iToBoS project

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.

The hospital operator interface on the final scanner

28/01/2025.

The start, preparation and validation of the data acquisition will be commanded by the HMI, the Hospital Operator Interface. This interface is crucial as it serves as the primary point of control and interaction for medical professionals during the scanning process.

Participate in the iToBoS Skin Lesion Detection Challenge!

24/01/2025.

Skin cancer is one of the most prevalent forms of cancer globally, reaching epidemic proportions.

Implications for Policy, Practice, and Further Research for Generative AI in Art Therapy for Melanoma Patients

21/01/2025.

The emergence of AI-generated art within therapeutic settings necessitates the establishment of guidelines to address ethical and privacy concerns including informed consent, data protection, and the confidentiality of patients’ medical images and resultant artworks.

Video presentation of the iToBoS challenge

17/01/2025.

The goal of this competition is to develop state-of-the-art machine learning techniques for detecting multiple skin lesions in clinical images.

Patient protection in the final scanner

15/01/2025.

The design of the iToBoS scanner places a strong emphasis on patient protection, particularly in the context of its robotic components operating in close proximity to the patient. 

More on perspectives for Generative AI-Assisted Art Therapy for melanoma patients

9/01/2025.

The COVID-19 pandemic accelerated the adoption of digital technologies in many areas of medicine.