AIMC Topic: Pregnancy

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Fada: Fetal Accurate Detection AI for Automated Ultrasound Image Analysis and Reporting.

Studies in health technology and informatics
This study introduces Fetal Accurate Detection AI (FADA) an advanced AI-driven framework for generating clinically relevant descriptions from fetal ultrasound images, specifically focused on diverse anatomical structures and views, including trans-ab...

Predicting Postpartum Depression Risk Using Social Determinants of Health.

Studies in health technology and informatics
Postpartum depression (PPD) affects approximately 20% of women after childbirth and has complex etiology. Existing predictive models of PPD lack training on large, national datasets and comprehensive integration of clinical and social determinants. T...

AI Bias and Confounding Risk in Health Feature Engineering for Machine Learning Classification Task.

Studies in health technology and informatics
Recent advancements in machine learning bring unique opportunities in health fields but also pose considerable challenges. Due to stringent ethical considerations and resource constraints, health data can vary in scope, population coverage, and colle...

Predicting time to live birth with deep learning embryo ranking: a novel multiple imputation approach.

Human reproduction (Oxford, England)
STUDY QUESTION: What is the clinical utility of embryo selection algorithms in estimating the time to live birth (TTLB)?

Information about labor epidural analgesia: an updated evaluation on the readability, accuracy, and quality of ChatGPT responses incorporating patient preferences and complex clinical scenarios.

International journal of obstetric anesthesia
BACKGROUND: Recent studies evaluating frequently asked questions (FAQs) on labor epidural analgesia (LEA) only used generic questions without incorporating detailed clinical information that reflects patient-specific inputs. We investigated the perfo...

Incorporating machine learning and statistical methods to address maternal healthcare disparities in US: A systematic review.

International journal of medical informatics
BACKGROUND: Maternal health disparities are recognized as a significant public health challenge, with pronounced disparities evident across racial, socioeconomic, and geographic dimensions. Although healthcare technologies have advanced, these dispar...

[A multi-feature fusion-based model for fetal orientation classification from intrapartum ultrasound videos].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVES: To construct an intelligent analysis model for classifying fetal orientation during intrapartum ultrasound videos based on multi-feature fusion.

A negative combined effect of exposure to maternal Mn-Cu-Rb-Fe metal mixtures on gestational anemia, and the mediating role of creatinine in the Guangxi Birth Cohort Study (GBCS): Twelve machine learning algorithms.

Ecotoxicology and environmental safety
The link between individual metals and gestational anemia has been established, but the impact of metal mixtures and the mediating role of renal function on gestational anemia remain inconclusive. The concentrations of 20 blood essential trace and no...

Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.

Diabetes technology & therapeutics
Since the discovery of the life-saving hormone insulin in 1921 by Dr. Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longer, healthie...

Incorporating end-user perspectives into the development of a machine learning algorithm for first time perinatal depression prediction.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental health conditions. These algorithms are often developed without considering the perspectives of the affected populations. This study describes the process ...