AI Medical Compendium Journal:
Birth defects research

Showing 1 to 7 of 7 articles

Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data.

Birth defects research
BACKGROUND: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) collects data abstracted from medical records and birth defects registries on pregnant people and their infants to understand outcomes associated with ...

Society for birth defects research and prevention's multidisciplinary research needs workshop 2022: A call to action.

Birth defects research
The Society for Birth Defects Research and Prevention (BDRP) strives to understand and protect against potential hazards to developing embryos, fetuses, children, and adults by bringing together scientific knowledge from diverse fields. The theme of ...

Regenerative robotics.

Birth defects research
Congenital diseases requiring reconstruction of parts of the gastrointestinal tract, skin, or bone are a challenge to alleviate especially in rapidly growing children. Novel technologies may be the answer. This article presents the state-of-art in re...

A machine learning approach to investigate potential risk factors for gastroschisis in California.

Birth defects research
BACKGROUND: To generate new leads about risk factors for gastroschisis, a birth defect that has been increasing in prevalence over time, we performed an untargeted data mining statistical approach.

Machine Learning and Natural Language Processing to Improve Classification of Atrial Septal Defects in Electronic Health Records.

Birth defects research
BACKGROUND: International Classification of Disease (ICD) codes can accurately identify patients with certain congenital heart defects (CHDs). In ICD-defined CHD data sets, the code for secundum atrial septal defect (ASD) is the most common, but it h...

Exploring Ensemble Learning Techniques for Infant Mortality Prediction: A Technical Analysis of XGBoost Stacking AdaBoost and Bagging Models.

Birth defects research
BACKGROUND: Infant mortality remains a critical public health issue, reflecting the overall health and well-being of a population. Accurate prediction of infant mortality is crucial, as it enables healthcare providers to identify at-risk populations ...

A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes.

Birth defects research
BACKGROUND: International Classification of Diseases (ICD) codes utilized for congenital heart defect (CHD) case identification in datasets have substantial false-positive (FP) rates. Incorporating machine learning (ML) algorithms following case sele...