Letizia Gionfrida

Imperial College London

Letizia Gionfrida

Arthronica™ an all-in-one AI platform that predicts musculoskeletal disorders through machine learning and computer vision.

Arthronica™ is a monitoring and rehabilitation platform that uses computer vision, an AI technology that allows computers to understand and label images, to allow remote assessment and self-management of clinical conditions.

Current arthritis assessment is based on subjective scoring with high intra/inter reader variability, highly skilled expert time and patient travel, and low sampling frequency (i.e. monthly or quarterly assessments). The consequences; a heightened probability of failed clinical trials, increased costs, and excessive complexity in disease management.

Arthronica™ enables ubiquitous technologies to extract quantifiable objective biomarkers to monitor chronic conditions, and facilitate rehabilitation protocols.

We believe in a future whereby patient monitoring with be automated. People will be able to manage their conditions from the comfort of their homes. For healthcare providers, remote monitoring and rehabilitation will free specialist capacity. Furthermore, our technology will extend the application of telemedicine and remote consultations. Data collection and analysis by our AI tool will facilitate faster, more efficient, cheaper and more accurate methods of validating new drugs, while improving health and providing better, safer, sustainable care for all.

Conected Mentors

Paul Dowling


Showcasing Success – Accelerating Pioneering MedTech

The medical technologies on Cohort One are as diverse as the institutions involved; including a robotic liner to improve the experience of using prosthetic limbs, an AI platform for assessing musculoskeletal disorders and rapid low-cost diagnostics for Tuberculosis.

Read about the successes of Cohort One