AIMC Topic: Infant, Newborn

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Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.

European radiology
OBJECTIVES: To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity ...

Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort study.

Reproductive biomedicine online
RESEARCH QUESTION: What is the pregnancy and neonatal outcomes of an interpretable artificial intelligence (AI) model for embryo selection in a prospective clinical trial?

Infant death prediction using machine learning: A population-based retrospective study.

Computers in biology and medicine
BACKGROUND: Despite declines in infant death rates in recent decades in the United States, the national goal of reducing infant death has not been reached. This study aims to predict infant death using machine-learning approaches.

The future of artificial intelligence in clinical nutrition.

Current opinion in clinical nutrition and metabolic care
PURPOSE OF REVIEW: Artificial intelligence has reached the clinical nutrition field. To perform personalized medicine, numerous tools can be used. In this review, we describe how the physician can utilize the growing healthcare databases to develop d...

Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: This study aims to investigate non-invasive electrocardiography as a method for the detection of congenital heart disease (CHD) with the help of artificial intelligence.

Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Neonatology
Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, and treatment. Artificial intelligence is a valuable tool that clinicians employ to reduce the scree...

Unsupervised abnormality detection in neonatal MRI brain scans using deep learning.

Scientific reports
Analysis of 3D medical imaging data has been a large topic of focus in the area of Machine Learning/Artificial Intelligence, though little work has been done in algorithmic (particularly unsupervised) analysis of neonatal brain MRI's. A myriad of con...

Artificial intelligence in the neonatal intensive care unit: the time is now.

Journal of perinatology : official journal of the California Perinatal Association
Artificial intelligence (AI) has the potential to revolutionize the neonatal intensive care unit (NICU) care by leveraging the large-scale, high-dimensional data that are generated by NICU patients. There is an emerging recognition that the confluenc...

Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units.

Jornal de pediatria
OBJECTIVE: To describe the challenges and perspectives of the automation of pain assessment in the Neonatal Intensive Care Unit.

Immune modulation by nutritional intervention in malnourished children: Identifying the phenotypic distribution and functional responses of peripheral blood mononuclear cells.

Scandinavian journal of immunology
Malnourished children are susceptible to an increased risk of mortality owing to impaired immune functions. However, the underlying mechanism of altered immune functions and its interaction with malnutrition is poorly understood. This study investiga...