AI Medical Compendium Journal:
American journal of perinatology

Showing 1 to 10 of 10 articles

Use of Artificial Intelligence in Recognition of Fetal Open Neural Tube Defect on Prenatal Ultrasound.

American journal of perinatology
To compare the axial cranial ultrasound images of normal and open neural tube defect (NTD) fetuses using a deep learning (DL) model and to assess its predictive accuracy in identifying open NTD.It was a prospective case-control study. Axial trans-tha...

Machine Learning for the Prediction of Surgical Morbidity in Placenta Accreta Spectrum.

American journal of perinatology
OBJECTIVE:  We sought to create a machine learning (ML) model to identify variables that would aid in the prediction of surgical morbidity in cases of placenta accreta spectrum (PAS).

Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.

American journal of perinatology
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...

Exploring the Limits of Artificial Intelligence for Referencing Scientific Articles.

American journal of perinatology
OBJECTIVE:  To evaluate the reliability of three artificial intelligence (AI) chatbots (ChatGPT, Google Bard, and Chatsonic) in generating accurate references from existing obstetric literature.

Identifying ChatGPT-Written Patient Education Materials Using Text Analysis and Readability.

American journal of perinatology
OBJECTIVE:  Artificial intelligence (AI)-based text generators such as Chat Generative Pre-Trained Transformer (ChatGPT) have come into the forefront of modern medicine. Given the similarity between AI-generated and human-composed text, tools need to...

Artificial Intelligence to Determine Fetal Sex.

American journal of perinatology
OBJECTIVE:  This proof-of-concept study assessed how confidently an artificial intelligence (AI) model can determine the sex of a fetus from an ultrasound image.

A Machine Learning Algorithm using Clinical and Demographic Data for All-Cause Preterm Birth Prediction.

American journal of perinatology
OBJECTIVE: Preterm birth remains the predominant cause of perinatal mortality throughout the United States and the world, with well-documented racial and socioeconomic disparities. To develop and validate a predictive algorithm for all-cause preterm ...

Applying Automated Machine Learning to Predict Mode of Delivery Using Ongoing Intrapartum Data in Laboring Patients.

American journal of perinatology
OBJECTIVE: This study aimed to develop and validate a machine learning (ML) model to predict the probability of a vaginal delivery (Partometer) using data iteratively obtained during labor from the electronic health record.

Procalcitonin as Predictor of Bacterial Infection in Meconium Aspiration Syndrome.

American journal of perinatology
BACKGROUND: There is a lack of definite consensus on indications for initiating antibiotics in neonates with meconium aspiration syndrome (MAS), instigating researchers to search for a biomarker that can help differentiate MAS from MAS with bacterial...

Stroke Volume Recruitability during the Third Trimester of Pregnancy.

American journal of perinatology
OBJECTIVE: It is unknown whether the heart operates in the ascending or flat portion of the Starling curve during normal pregnancy. Pregnant women do not respond to the passive leg-raising maneuver secondary to mechanical obstruction of the inferior ...