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Ultrasonography, Prenatal

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Performance of ChatGPT and Microsoft Copilot in Bing in answering obstetric ultrasound questions and analyzing obstetric ultrasound reports.

Scientific reports
To evaluate and compare the performance of publicly available ChatGPT-3.5, ChatGPT-4.0 and Microsoft Copilot in Bing (Copilot) in answering obstetric ultrasound questions and analyzing obstetric ultrasound reports. Twenty questions related to obstetr...

AI and early diagnostics: mapping fetal facial expressions through development, evolution, and 4D ultrasound.

Journal of perinatal medicine
The development of facial musculature and expressions in the human fetus represents a critical intersection of developmental biology, neurology, and evolutionary anthropology, offering insights into early neurological and social development. Fetal fa...

The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review.

Medicina (Kaunas, Lithuania)
Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this review paper, we first outline the technical background of AI and echocardiography and then present an a...

Effectiveness and clinical impact of using deep learning for first-trimester fetal ultrasound image quality auditing.

BMC pregnancy and childbirth
BACKGROUND: Regular auditing of ultrasound images is required to maintain quality; however, manual auditing is time-consuming and can be inconsistent. We therefore aimed to develop and validate an artificial intelligence-based image quality audit (AI...

Automatic Human Embryo Volume Measurement in First Trimester Ultrasound From the Rotterdam Periconception Cohort: Quantitative and Qualitative Evaluation of Artificial Intelligence.

Journal of medical Internet research
BACKGROUND: Noninvasive volumetric measurements during the first trimester of pregnancy provide unique insight into human embryonic growth and development. However, current methods, such as semiautomatic (eg, virtual reality [VR]) or manual segmentat...

Towards automatic US-MR fetal brain image registration with learning-based methods.

NeuroImage
Fetal brain imaging is essential for prenatal care, with ultrasound (US) and magnetic resonance imaging (MRI) providing complementary strengths. While MRI has superior soft tissue contrast, US offers portable and inexpensive screening of neurological...

Prediction of clinical risk factors in pregnancy using optimized neural network scheme.

Placenta
Women should be aware of prenancy related health issues. A user-friendly model is developed in which the patients can use as well as clinicians to determine the risks associated with foetal development inside the womb, birth weight, whose effects are...

[Artificial intelligence and ultrasound in fetal medicine].

Ugeskrift for laeger
Ultrasound is essential in fetal medicine for diagnosing and monitoring, but it requires extensive training. Artificial intelligence (AI) shows a great promise in enhancing the clinical training and practice, by improving workflow and standardising d...

Artificial intelligence based automatic classification, annotation, and measurement of the fetal heart using HeartAssist.

Scientific reports
This study evaluated the feasibility of HeartAssist, a novel automated tool designed for classification of fetal cardiac views, annotation of cardiac structures, and measurement of cardiac parameters. Unlike previous AI tools that primarily focused o...

Fetal origins of adult disease: transforming prenatal care by integrating Barker's Hypothesis with AI-driven 4D ultrasound.

Journal of perinatal medicine
INTRODUCTION: The fetal origins of adult disease, widely known as Barker's Hypothesis, suggest that adverse fetal environments significantly impact the risk of developing chronic diseases, such as diabetes and cardiovascular conditions, in adulthood....