Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography - Scorecard - MDSpire

Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography

  • By

  • Angelica Willis

  • Chace Lee

  • Justin Krogue

  • Anneka Wickramanayake

  • Nichole Young-Lin

  • Stacey Caron

  • Priscah Cheruiyot

  • Amber Watters

  • Alicia Martín

  • Tiya Tiyasirichokchai

  • Akib Uddin

  • Yun Liu

  • Patricia Strachan

  • Sunny Jansen

  • Alyssa Santi

  • Preeti Singh

  • Catherine Arguelles

  • Kenneth Hudson

  • David Melnick

  • Mahesh Vaidyanathan

  • Mozziyar Etemadi

  • Yossi Matias

  • Avinatan Hassidim

  • Greg S. Corrado

  • Shruthi Prabhakara

  • Daniel Golden

  • Ryan G. Gomes

  • Shravya Shetty

  • July 9, 2026

  • 0 min

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Clinical Scorecard: Expansion of AI-Driven Gestational Age Evaluation Through Blind Sweep Ultrasound Techniques

At a Glance

CategoryDetail
ConditionGestational Age Estimation
Key MechanismsAI-driven analysis of blind sweep ultrasonography scans for accurate gestational age determination.
Target PopulationPregnant individuals aged 18 years or older with gestational age between 16 weeks 0 days and 39 weeks 6 days.
Care SettingMulticenter observational diagnostic study in clinical environments.

Key Highlights

  • AI systems can improve access to prenatal ultrasonography in low-resource settings.
  • Blind sweep ultrasonography does not require real-time imaging interpretation.
  • The study evaluates AI model generalizability across different clinical settings.
  • Participants received standard-of-care ultrasonography within 1 week of blind sweep examination.
  • The model predicts gestational age using sonographer-acquired video clips.

Guideline-Based Recommendations

Diagnosis

  • Gestational age should be determined using early dating scans before 22 weeks.

Management

  • AI models can assist in timing obstetric care and managing high-risk conditions.

Monitoring & Follow-up

  • Follow-up on ultrasonography findings and birth outcomes through delivery.

Risks

  • Potential complications from inaccurate gestational age estimation.

Patient & Prescribing Data

Pregnant individuals with clinically confirmed pregnancies.

AI-driven ultrasound techniques may enhance prenatal care delivery.

Clinical Best Practices

  • Utilize AI models for gestational age estimation in diverse clinical environments.
  • Incorporate standard-of-care ultrasonography for comparison with AI predictions.

Related Resources & Content

Original Source(s)

Generalization of AI-Based Gestational Age Assessment Using Blind Sweep Ultrasonography

  • by Angelica Willis, Chace Lee, Justin Krogue, Anneka Wickramanayake, Nichole Young-Lin, Stacey Caron, Priscah Cheruiyot, Amber Watters, Alicia Martín, Tiya Tiyasirichokchai, Akib Uddin, Yun Liu, Patricia Strachan, Sunny Jansen, Alyssa Santi, Preeti Singh, Catherine Arguelles, Kenneth Hudson, David Melnick, Mahesh Vaidyanathan, Mozziyar Etemadi, Yossi Matias, Avinatan Hassidim, Greg S. Corrado, Shruthi Prabhakara, Daniel Golden, Ryan G. Gomes, Shravya Shetty

  • July 9, 2026

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