The research develops digital tools for the early detection of infection risk in chronic skin ulcers, integrating thermal imaging, RGB images and artificial intelligence.

The goal is to support clinicians with a non invasive, rapid and radiation free system capable of identifying thermal alterations associated with inflammatory processes and providing objective indicators to support screening.

Preliminary results confirm the feasibility of the approach and guide future activities toward dataset expansion, further integration of thermal and visual data, and validation on independent cohorts.

The research develops digital tools for the automated assessment of neoplastic risk in skin ulcers, based on the analysis of wound images.

The goal is to support clinicians in screening between benign chronic ulcers and potentially neoplastic lesions, identifying high risk cases without initially relying on invasive procedures. The approach uses artificial intelligence to analyze morphological features of the lesion, such as wound edges, wound bed and perilesional tissue, providing an interpretable risk stratification that can support clinical practice.

Future perspectives include dataset expansion, integration into the clinical workflow and validation on additional independent cohorts.

Thermal Matrix is a project developed in collaboration with Skin Plastic Lab, dedicated to the creation of a new generation of intelligent tools for wound monitoring and postoperative recovery.

The platform integrates advanced sensors, artificial intelligence, analysis software and data visualization systems to collect and interpret physiological information in a non invasive way.

The goal is to support physicians and healthcare professionals in assessing the healing process through objective, repeatable and easily interpretable indicators, helping to reduce reliance on purely subjective observations and enabling the early identification of possible complications.

Through technological innovation and advanced data analysis, Thermal Matrix aims to improve clinical monitoring, optimize care pathways and provide decision support tools for healthcare that is increasingly effective, standardized and focused on prevention.