Pocus-AI
Artificial intelligence in ultrasound telemedicine for early diagnosis in gynecology at the point of care
Scheda del progetto
SynDiag S.r.l.
TESI T4MED S.r.l.
In gynecology, various conditions such as endometriosis, ovarian cysts, and ovarian cancer can severaly impact a woman's quality of life. Although ultrasound is the primary diagnostic tools, it requires interpretation by experienced physicians, and 75% of ovarian cancer cases are diagnosed late, with low survivial rates. The Pocus-AI project is the result of a partnership between TESI4MED and Syndiag that combines T4MED expertise in digital logistic and telemedicine with SynDiag's innovative OvAi software for early and accurare diagnosis of ovarian cancer diagnosis. This collaboration aims to improve healthcare management and enhance patient survival rates.
Contact:
Daniele Conti
The Pocus-AI project proposes the use of artificial intelligence and telemedicine to enhance ultrasound diagnosis, making the execution of ultrasound exams accessible event to non-medical personnel. These exams will be evaluated by expert gynecologists with the assistance of AI algorithms to prioritize suspicious ovarian cysts.
The OvAi platform offers various products for gynecologists, including the Academy for training, DiGyn for managing and telemedicine consultations of ultrasound exams, and OvAi Focus and OvAi X for diagnostic support through artificial intelligence.
DiGyn allows the management of clinical and ultrasound data and the organization of visits, while OvAi Focus provides objective information on the morphological characteristics of ovarian cysts.
OvAi X, currently undergoing certification as a medical device, uses artificial intelligence algorithms for differential diagnosis of ovarian masses. The TESI eViSuS platform provides solutions for teletraining, teleconsultation and telemonitoring of patients.
The project has significant scientific, economic and social implications. It utilizes artificial intelligence to enhance ultrasound interpretation, democratizing access to effective healthcare solutions. This has the potential to open new markets and improve the efficiency of the healthcare system by reducing waiting times and enhancing case management. Additionally, it provides a more timely and accurate service for patients, especially those with a genetic risk of ovarian cancer, enabling early diagnosis and improving quality of life.