doctors in front of digital space
English

Omnia: the multidisciplinary approach to the patient through Lucrez-IA

25.02.2025

Italian version 

Fabrizio Dal Moro, director of Urology at the University Hospital of Padua, has implemented the Omnia project thanks to Lucrez-IA, the artificial intelligence developed by the University of Padua, to improve the multidisciplinary approach to personalised medicine.

The initiative aims to compare data and indications from various medical specialties to make diagnoses and therapies more efficient.

The guidelines recommend that diagnostic and therapeutic decisions for most diseases be made after a multidisciplinary meeting between various specialists to compare different perspectives and data. Artificial intelligence, trained with all available guidelines, can simplify this comparison by identifying the best diagnostic and therapeutic strategies, also considering non-surgical parameters such as cardiovascular risk.

Artificial intelligence will intervene only after the multidisciplinary team has formulated its conclusions, assisting in comparing the proposed solutions and thus identifying the best diagnostic and therapeutic strategies.
Manually comparing all the guidelines is often complex and time-consuming.
"This is why we decided to entrust this complex task to artificial intelligence: all available information for a specific clinical case will be entered anonymously, allowing the artificial intelligence to identify the key parameters and list possible diagnostic and therapeutic strategies, providing percentages of diagnostic accuracy, favourable or unfavourable outcomes, probabilities of complications, and more," explains Fabrizio Dal Moro.

"We have also decided to compare the well-known ChatGPT engine with the Lucrez-IA artificial intelligence developed by the University of Padua," adds the professor, because "the analysis of the data collected by comparing the two systems will be very useful for better understanding the areas that need improvement."

Omnia involves an assessment of each clinical case using all evidence-based tools available. All information entered into the two artificial intelligence systems will be completely anonymous to ensure patient privacy.