Catalyst Awardee

Project Description

Explainable Artificial Intelligence for Early Diagnosis of Gynecological Cancer during Sonography

Daniele Conti, PhD; Rosilari Bellacosa Marotti, PhD; Federica Gerace, PhD

Competition Sponsor: EIT Health of the European Union

SynDiag brings a new mindset to diagnose ovarian cancers early, putting Artificial Intelligence at the service of gynecology. Sonography is the primary level of medical investigation for most of women’s oncologic diseases, particularly for ovarian cancer, the most lethal tumor pathology for women, whose incidence increases dramatically with aging and leads each year to about 300.000 new cases worldwide and more than 170.000 deaths. Nevertheless, since sonography is intrinsically user dependent and requires a subjective evaluation of variables, the correctness and quality of the diagnosis mainly relies on the physician’s experience.
Today there is no instrument that supports gynecologists in sonography interpretation. SynDiag’s GynAi cloud platform provides a software, OvAi, for clinical decision support based on AI, and the Academy for Digital Gynecology, a new learning platform based on digital peer learning.
Thousands of high-quality clinical cases have been collected by world-class hospitals to train GynAi as an expert system based on state of the art algorithms and according to international guidelines for clinical evaluation. OvAi highlights relevant features to be considered for definitive diagnosis, proposes a malignancy risk of ovarian cancer and makes it evident to the physician the sonographic features considered that led to such a second opinion, without changing clinical practice and leaving the gynecologists the final decision.
GynAi is a solution designed to provide decision support systems based on AI and advanced peer learning for physicians training for all conditions in gynecology, starting from Ovarian Cancer and then expanding to Uterine and Pelvis conditions.

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