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Sonio: Deep-Learning for Detection and Diagnostic of Prenatal Malformations

Objective

1 child out of 33 is born with a congenital malformation in developed countries, leading to mortality & disability which impact the children, the families & healthcare system. Fetal ultrasound is the standard non invasive examination to screen for malformations, but 50% of malformations are not detected at routine exams as fetal ultrasound is very complex, time-consuming & highly operator-dependent. One needs to acquire the right images, interpret them & combine them with blood or/and genetic tests to get the right diagnosis.
We created Sonio, an AI one-stop modular software platform to guide OBGYNS & sonographers during fetal ultrasound. The core is the Clinical Brain, a unique mix between fetal medicine & AI, aware of 1.6k anomalies & 450 syndromes. It can prioritize anomalies to identify the most probable diagnoses based on medical history & observed phenotype. With EIC support, we will fully build image recognition & genomics into our platform to revolutionize prenatal diagnosis.

Coordinator

SONIO
Net EU contribution
€ 2 500 000,00
Address
24 RUE DU FAUBOURG SAINT-JACQUES
75014 Paris
France

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Ile-de-France Ile-de-France Paris
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Links
Total cost
€ 5 717 542,50