We have several ongoing activities concerning health applications.
Neurodegenerative disorders (ND) encompass a wide range of conditions resulting from progressive damage to the cells and connections of the nervous system that are essential for mobility, coordination, strength, sensation and cognition.
We aim to address the early detection of ND using speech and writing.
In particular, we aim to build an automatic ND detection tool based on the speech signal, which can achieve high performance in noisy conditions by exploiting speech attributes, i.e. articulatory features, and which can work in interlingual scenarios.
In addition, we aim to develop tools to support early diagnosis and progression of NDs through handwriting analysis from online coordinates, offline images and RGCs.
The last instrument is in the patent phase.
Cancer is the second most common cause of death globally and involves highly variable clinical and biological scenarios.
Our goal is to build an automated or semi-automated and interactive approach based on artificial intelligence techniques to segment masses on dynamic contrast-enhanced breast MRI (DCE) and compare it with existing approaches based on classical image processing.
The proposed computerised approach could be implemented in clinical research environments by providing a reliable volumetric and radiomic analyses tool.
Due to the rapid progression of the disease worldwide, many have been working on solutions for the rapid and reliable detection of COVID-19.
We investigated and developed an artificial intelligence-based system for the early diagnosis of COVID-19 and certain types of pneumonia from chest X-ray images of people with suspected SARS-CoV-2 infection.
Despite their lower information content, X-ray imaging offers several advantages such as a lower radiation dose, lower costs for both the patient and the healthcare system, higher general availability and greater accessibility of equipment.
The solution achieves good accuracy, is cost-effective and reduces workload and patient-side impact.