Ki Hoon Ahn — Endo Lab

2024

Ultrasonographic assessment of abnormal fetal growth related to uteroplacental-fetal biometrics and Doppler (U-AID) indices: Protocol for multicenter retrospective cohort study trial.

PloS one ·doi:10.1371/journal.pone.0298060

Fetal growth restriction (FGR) is one of the leading causes of perinatal morbidity and mortality. Many studies have reported an association between FGR and fetal Doppler indices focusing on umbilical artery (UA), middle cerebral artery (MCA…

2023

A Randomized, Multicenter, Double-Blind, Parallel, Non-Inferiority Clinical Study to Compare the Efficacy and Safety of Unicenta and Melsmon for Menopausal Symptom Improvement.

Medicina (Kaunas, Lithuania) ·doi:10.3390/medicina59081382

This study was conducted to evaluate the efficacy and safety of Unicenta in female subjects with menopausal symptoms by analyzing the changes in the Kupperman index (primary endpoint) and hormonal changes (secondary endpoint). It was a rand…

2023

Association between early preterm birth and maternal exposure to fine particular matter (PM10): A nation-wide population-based cohort study using machine learning.

PloS one ·doi:10.1371/journal.pone.0289486

Although preterm birth (PTB), a birth before 34 weeks of gestation accounts for only less than 3% of total births, it is a critical cause of various perinatal morbidity and mortality. Several studies have been conducted on the association b…

2023

Associations of Preterm Birth with Dental and Gastrointestinal Diseases: Machine Learning Analysis Using National Health Insurance Data.

International journal of environmental research and public health ·doi:10.3390/ijerph20031732

BackgroundThis study uses machine learning with large-scale population data to assess the associations of preterm birth (PTB) with dental and gastrointestinal diseases.MethodsPopulation-based retrospective cohort data came from Korea Nation…

2023

Preterm birth and maternal heart disease: A machine learning analysis using the Korean national health insurance database.

PloS one ·doi:10.1371/journal.pone.0283959

BackgroundMaternal heart disease is suspected to affect preterm birth (PTB); however, validated studies on the association between maternal heart disease and PTB are still limited. This study aimed to build a prediction model for PTB using …

2021

Association of Preterm Birth with Depression and Particulate Matter: Machine Learning Analysis Using National Health Insurance Data.

Diagnostics (Basel, Switzerland) ·doi:10.3390/diagnostics11030555

This study uses machine learning and population data to analyze major determinants of preterm birth including depression and particulate matter. Retrospective cohort data came from Korea National Health Insurance Service claims data for 405…

review 2020

Application of Artificial Intelligence in Early Diagnosis of Spontaneous Preterm Labor and Birth

Diagnostics ·doi:10.3390/diagnostics10090733

This study reviews the current status and future prospective of knowledge on the use of artificial intelligence for the prediction of spontaneous preterm labor and birth ("preterm birth" hereafter). The summary of review suggests that diffe…

2020

Determinants of Spontaneous Preterm Labor and Birth Including Gastroesophageal Reflux Disease and Periodontitis.

Journal of Korean medical science ·doi:10.3346/jkms.2020.35.e105

BackgroundPeriodontitis is reported to be associated with preterm birth (spontaneous preterm labor and birth). Gastroesophageal reflux disease (GERD) is common during pregnancy and is expected to be related to periodontitis. However, little…

article 2019

Artificial Neural Network Analysis of Spontaneous Preterm Labor and Birth and Its Major Determinants

Journal of Korean medical science ·doi:10.3346/jkms.2019.34.e128

BACKGROUND: Little research based on the artificial neural network (ANN) is done on preterm birth (spontaneous preterm labor and birth) and its major determinants. This study uses an ANN for analyzing preterm birth and its major determinant…