AI Medical Compendium Topic:
Pregnancy

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Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time.

Prenatal diagnosis
OBJECTIVE: Advances in artificial intelligence (AI) have demonstrated potential to improve medical diagnosis. We piloted the end-to-end automation of the mid-trimester screening ultrasound scan using AI-enabled tools.

Machine learning approach to needle insertion site identification for spinal anesthesia in obese patients.

BMC anesthesiology
BACKGROUND: Ultrasonography for neuraxial anesthesia is increasingly being used to identify spinal structures and the identification of correct point of needle insertion to improve procedural success, in particular in obesity. We developed an ultraso...

Learn Fine-Grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images.

IEEE journal of biomedical and health informatics
Automatic and accurate detection of anatomical landmarks is an essential operation in medical image analysis with a multitude of applications. Recent deep learning methods have improved results by directly encoding the appearance of the captured anat...

Should there be an "AI" in TEAM? Embryologists selection of high implantation potential embryos improves with the aid of an artificial intelligence algorithm.

Journal of assisted reproduction and genetics
PURPOSE: A deep learning artificial intelligence (AI) algorithm has been demonstrated to outperform embryologists in identifying euploid embryos destined to implant with an accuracy of 75.3% (1). Our aim was to evaluate the performance of highly trai...

Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
The incidence of infertility is continuously increasing nearly all over the world in recent years, and novel methods for accurate assessment are of great need. Artificial Intelligence (AI) has gradually become an effective supplementary method for th...

A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals.

Sensors (Basel, Switzerland)
The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents in...

Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis.

Scientific reports
The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed model...

Machine learning guided postnatal gestational age assessment using new-born screening metabolomic data in South Asia and sub-Saharan Africa.

BMC pregnancy and childbirth
BACKGROUND: Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, ad...

Use of an artificial intelligence-based rule extraction approach to predict an emergency cesarean section.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: One of the major problems with artificial intelligence (AI) is that it is generally known as a "black box". Therefore, the present study aimed to construct an emergency cesarean section (CS) prediction system using an AI-based rule extract...

Staged reflexive artificial intelligence driven testing algorithms for early diagnosis of pituitary disorders.

Clinical biochemistry
BACKGROUND: Sellar masses (SM) frequently present with insidious hormonal dysfunction. We previously showed that, by utilizing a combined reflex/reflecting approach involving a laboratory clinician (LC) on common endocrine test results requested by n...