Prenaital

About Prenaital

PRENAITAL develops AI models that enhance the early detection of high-risk pregnancies, identifying conditions such as growth retardation and macrosomia more effectively than current clinical practices. By improving prenatal diagnostics, PRENAITAL aims to reduce the incidence of maternal and fetal complications, including birth defects and chronic diseases.

```xml <problem> Despite widespread use of ultrasound examinations during pregnancy, current clinical practices often fail to identify a significant number of pregnancies at risk for adverse outcomes such as abnormal fetal growth and preterm birth. Existing prenatal screening methods may also overlook key patient factors, leading to disparities in the quality of care provided to diverse demographic groups. </problem> <solution> PRENAITAL develops AI-powered models to improve the early detection of high-risk pregnancies by analyzing population-wide data and enhancing ultrasound diagnostics. Their technology aims to reduce bias related to factors like BMI, age, race, and parity, ensuring more equitable and personalized prenatal care. By improving the accuracy of risk prediction, PRENAITAL enables clinicians to better plan the timing and mode of delivery, monitor fetal well-being, and optimize medical interventions, potentially preventing stillbirths and preterm births. The AI integrates into existing clinical workflows, acting as a support tool for risk assessment and quality assurance. </solution> <features> - AI models trained on population-wide data to improve ultrasound diagnostics - Increased sensitivity in identifying at-risk pregnancies compared to current clinical standards - Reduction of bias against specific demographic groups (BMI, age, race, parity) - Integration with existing clinical workflows and technology - Clinical support tool for risk assessment, second opinions, and quality assurance </features> <target_audience> The primary target audience includes healthcare providers, obstetricians, and hospitals seeking to improve the accuracy and equity of prenatal risk assessment and reduce adverse pregnancy outcomes. </target_audience> ```

What does Prenaital do?

PRENAITAL develops AI models that enhance the early detection of high-risk pregnancies, identifying conditions such as growth retardation and macrosomia more effectively than current clinical practices. By improving prenatal diagnostics, PRENAITAL aims to reduce the incidence of maternal and fetal complications, including birth defects and chronic diseases.

Where is Prenaital located?

Prenaital is based in Copenhagen, Denmark.

When was Prenaital founded?

Prenaital was founded in 2023.

How much funding has Prenaital raised?

Prenaital has raised 550000.

Who founded Prenaital?

Prenaital was founded by Tanja Danner and Aasa Feragen.

  • Tanja Danner - CEO
  • Aasa Feragen - Co-Founder of Prenaital
Location
Copenhagen, Denmark
Founded
2023
Funding
550000
Employees
8 employees
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Prenaital

Score: 77/100
AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

PRENAITAL develops AI models that enhance the early detection of high-risk pregnancies, identifying conditions such as growth retardation and macrosomia more effectively than current clinical practices. By improving prenatal diagnostics, PRENAITAL aims to reduce the incidence of maternal and fetal complications, including birth defects and chronic diseases.

prenaital.com300+
Founded 2023Copenhagen, Denmark

Funding

$

Estimated Funding

$550K+

Team (5+)

Tanja Danner

CEO

Aasa Feragen

Co-Founder of Prenaital

Company Description

Problem

Despite widespread use of ultrasound examinations during pregnancy, current clinical practices often fail to identify a significant number of pregnancies at risk for adverse outcomes such as abnormal fetal growth and preterm birth. Existing prenatal screening methods may also overlook key patient factors, leading to disparities in the quality of care provided to diverse demographic groups.

Solution

PRENAITAL develops AI-powered models to improve the early detection of high-risk pregnancies by analyzing population-wide data and enhancing ultrasound diagnostics. Their technology aims to reduce bias related to factors like BMI, age, race, and parity, ensuring more equitable and personalized prenatal care. By improving the accuracy of risk prediction, PRENAITAL enables clinicians to better plan the timing and mode of delivery, monitor fetal well-being, and optimize medical interventions, potentially preventing stillbirths and preterm births. The AI integrates into existing clinical workflows, acting as a support tool for risk assessment and quality assurance.

Features

AI models trained on population-wide data to improve ultrasound diagnostics

Increased sensitivity in identifying at-risk pregnancies compared to current clinical standards

Reduction of bias against specific demographic groups (BMI, age, race, parity)

Integration with existing clinical workflows and technology

Clinical support tool for risk assessment, second opinions, and quality assurance

Target Audience

The primary target audience includes healthcare providers, obstetricians, and hospitals seeking to improve the accuracy and equity of prenatal risk assessment and reduce adverse pregnancy outcomes.