AIMC Topic: Fetal Development

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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...

Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

Scientific reports
We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, using a prospective cross-center, multi-level approach. We developed, implemented, and tested a deep-l...

Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques.

Proteomics
The study of fetal gut development is critical due to its substantial influence on immediate neonatal and long-term adult health. Current research largely focuses on microbiome colonization, gut immunity, and barrier function, alongside the impact of...

Predicting newborn birth outcomes with prenatal maternal health features and correlates in the United States: a machine learning approach using archival data.

BMC pregnancy and childbirth
BACKGROUND: Newborns are shaped by prenatal maternal experiences. These include a pregnant person's physical health, prior pregnancy experiences, emotion regulation, and socially determined health markers. We used a series of machine learning models ...

Application of artificial neural networks to evaluate femur development in the human fetus.

PloS one
The present article concentrates on an innovative analysis that was performed to assess the development of the femur in human fetuses using artificial intelligence. As a prerequisite, linear dimensions, cross-sectional surface areas and volumes of th...

Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.

BMC pregnancy and childbirth
BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CU...

Recognition of facial expression of fetuses by artificial intelligence (AI).

Journal of perinatal medicine
OBJECTIVES: The development of the artificial intelligence (AI) classifier to recognize fetal facial expressions that are considered as being related to the brain development of fetuses as a retrospective, non-interventional pilot study.

Fetal brain age estimation and anomaly detection using attention-based deep ensembles with uncertainty.

NeuroImage
MRI-based brain age prediction has been widely used to characterize normal brain development, and deviations from the typical developmental trajectory are indications of brain abnormalities. Age prediction of the fetal brain remains unexplored, altho...

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study.

The Lancet. Digital health
BACKGROUND: Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal gestati...