How AI solutions radically improve detection of at-risk pregnancies

Using population-wide data, we leverage AI models to improve ultrasound diagnostics in 3 ways:

By targeting these 3 dependencies, we improve the fairness of prenatal diagnostics for different demographic groups, the quality of ultrasound scans, and the access to high-quality diagnostics for all.

We reduce the bias against certain groups (BMI, age, race, parity)

We reduce the need for highly trained ultrasound technicians

We enable high-quality diagnostics using any equipment

PRENAITAL impact 

In the US and Europe we have a total of 8 million pregnancies per year. More than 95% of these pregnancies receive 2 ultrasound examinations yet we still fail to identify more than half of pregnancies at risk of adverse outcomes. The AI models from PRENAITAL have shown a 25% increased sensitivity in identifying at-risk pregnancies. This could result in the prevention of 14.000 stillbirths and prevention og 10.800 preterm births.

The timely detection of abnormal growth has sereval benefit. Using AI models to improve ultrasound diagnostics we enable:

Planning time of birth

Planning mode of delivery

Monitoring fetal well-being through CTG and ultrasound

Medical optimization