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Artificial intelligence and rehabilitation medicine: the revolution has begun

Artificial intelligence (AI) is already a concrete reality at ISICO, where it is actively used in daily clinical practice, as a research tool in studies published in scientific journals, and as part of the European PREPARE project, in which our institute is a partner. AI is fundamentally transforming the work of rehabilitation professionals, opening up new possibilities in early diagnosis, patient monitoring, treatment personalisation, and therapeutic education.

The potential of AI is immense. In a context where the volume of clinical, instrumental and functional data is growing exponentially, intelligent algorithms allow for the rapid and efficient analysis of this information, turning it into tangible support for clinical decision-making.

“We are only at the beginning of a transformation that will become increasingly far-reaching,” explains Francesco Negrini, physiatrist at ISICO and Associate Professor at the University of Insubria.
“Just as the first computers revolutionised our work in the 1980s, AI is set to become an indispensable tool in the daily work of clinicians.”

In recent years, research on AI in the medical field has accelerated dramatically. Between 2022 and 2023 alone, funding in this sector increased eightfold, reaching $25 billion. Applications range from imaging diagnostics and outcome prediction to motor rehabilitation support and functional assessment.

ISICO has contributed to this evolution. One example is a 2023 study on the use of AI to improve scoliosis screening. The team developed an algorithm capable of combining multiple variables (ATR, age, sex, BMI, family history, prominence height, curve location) to detect the condition early — going beyond the limitations of traditional tools like the scoliometer.

But AI’s applications in rehabilitation go far beyond scoliosis. Through data collection from wearable sensors, surface electromyography, and robotic devices, it is now possible to analyse patients’ movements in real time, support the monitoring of gait and speech disorders, classify levels of motor dysfunction, and adapt treatment plans in a truly personalised way.

At ISICO, AI is also used to enhance the patient experience through projects such as ISAIA (ISICO AI Assistant) — a virtual assistant designed to improve communication between clinicians and patients, answer frequently asked questions, and support the management of emails and FAQs. This approach helps maintain an informative and educational dialogue beyond the consultation, responding to patients’ ongoing concerns during treatment.

Another promising frontier is the integration of AI into telerehabilitation. Smartwatches and dedicated apps now make it possible to monitor home exercises with precision, optimising therapeutic pathways remotely. One recent study, for instance, demonstrated that AI could automatically recognise post-stroke rehabilitation exercises with over 99% accuracy.

Of course, with opportunity comes challenge. The handling of sensitive data, the lack of transparency in algorithms (often still “black boxes”), the risk of over-reliance on automated solutions, and the quality of training data are all critical issues requiring careful oversight and regulation. A responsible adoption of AI must be grounded in strong clinical supervision, ongoing human oversight, and the scientific quality of the sources used.

In conclusion, artificial intelligence will not replace clinicians — it will support them, helping them become more accurate, more efficient, and better equipped to offer truly personalised care.
At ISICO, that revolution has already begun.

SOSORT Conference: Isico in the front row

Once again, ISICO receives the acceptance, in the form of an oral presentation or a poster, of all nine abstracts submitted for the next annual international conference SOSORT that will be held from May 1 to May 4 in Boston, United States.

This is a reconfirmation with full marks for Isico, among the best researchers in the world in the rehabilitation treatment of spinal pathologies.
The following abstracts will be presented, where the first authors Dr. Fabio Zaina, Dr. Greta Jurenaite and Dr. Carlotte Kiekens, physiatrists, Michele Romano, director of physiotherapy, Giulia Fregna, physiotherapist, are from Isico further to Claudio Cordani, a physiotherapist.

Normative data for radiographic sagittal parameters in asymptomatic population from childhood to adulthood: a systematic search and review (oral presentation)

Lessons learned on trunk neurophysiology and motor control from adolescent idiopathic scoliosis. A scoping review (poster)

Influence of specific interventions on bracing compliance in adolescents with idiopathic scoliosis. A systematic review of the literature including sensors’ monitoring (oral presentation)

Can currently used questionnaires like ODI (and SRS-22) discriminate patients with scoliosis in a population with chronic back pain? (oral presentation)

Personal and clinical determinants of brace wearing time in adolescents with idiopathic scoliosis (oral presentation)

Convexity orientation of single scoliotic curves. Are they as we have always been taught? Verification of 4470 single curves (oral presentation)

Suspected high prevalence and gender difference of scoliotic curves with the apex at T12 (poster)

PREPARE: Personalized rehabilitation via novel AI patient stratification strategies – the case for idiopathic scoliosis during growth (poster)

Case series report of atypical lumbar Scheuermann’s disease treated with braces and physiotherapeutic specific exercises (poster)

One of the 9 abstracts presented is linked to the European project PREPARE, in which ISICO takes part.

PREPARE Rehab aims to provide healthcare professionals with valuable insights and tools to predict better and stratify patients, ultimately leading to more personalized and effective rehabilitation interventions. Artificial Intelligence (AI) may help predict treatment outcomes and improve rehabilitation strategies for Idiopathic Scoliosis.

“By combining different factors that influence treatment success, AI-based models can provide a better understanding of the natural progression of the disease and the factors that determine the effectiveness of treatments. This allows us to personalize therapies better and avoid both over-treatment and under-treatment  – explains Dr. Carlotte Kiekens, one of the researchers of this project. With its ability to analyze large amounts of data and utilize deep learning techniques, AI offers a comprehensive approach to predicting functional prognosis and setting goals in Individual Rehabilitation Projects (IRPs)”.
In this study, data from over 21 thousand patients were taken into consideration. What do we expect to achieve?
“Three results: a clinical decision support system to be used by clinicians to make shared decisions with their patients and families, integrating big data and thus providing real-time insights; the development of innovative methods and models for categorizing patients into different groups based on specific criteria – ends Dr. Kiekens – and a roadmap that outlines the steps and requirements for ensuring compliance with medical device regulations.  These expected results indicate a comprehensive approach to improving healthcare through the integration of advanced technology, data analytics, and regulatory compliance measures”.