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Public Health Genomics and Precision Health Knowledge Base (v9.0)
PHGKB
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Public Health Genomics Branch
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: Apr 30, 2024
. (Total: 63724 Documents since 2012)
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Medication Usage Record-Based Predictive Modeling of Neurodevelopmental Abnormality in Infants under One Year: A Prospective Birth Cohort Study.
Tianyi Zhou et al. Healthcare (Basel) 2024 12(7)
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Predictive value of ultrasonic artificial intelligence in placental characteristics of early pregnancy for gestational diabetes mellitus.
Huien Zhou et al. Front Endocrinol (Lausanne) 2024 151344666
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Artificial intelligence in imaging in the first trimester of pregnancy: a systematic review.
Emma Umans et al. Fetal Diagn Ther 2024
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Predicting risk of preterm birth in singleton pregnancies using machine learning algorithms.
Qiu-Yan Yu et al. Front Big Data 2024 71291196
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Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach.
J Xing et al. J Endocrinol Invest 2024
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Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.
Chen Wang et al. Fertil Steril 2024
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Deep Survival Analysis for Interpretable Time-Varying Prediction of Preeclampsia Risk.
Braden W Eberhard et al. medRxiv 2024
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Recommendations for initial diabetic retinopathy screening of diabetic patients using large language model-based artificial intelligence in real-life case scenarios.
Nikhil Gopalakrishnan et al. Int J Retina Vitreous 2024 10(1) 11
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Prediction of 2-Year Cognitive Outcomes in Very Preterm Infants Using Machine Learning Methods.
Andrea K Bowe et al. JAMA Netw Open 2023 6(12) e2349111
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Predicting preterm birth using explainable machine learning in a prospective cohort of nulliparous and multiparous pregnant women.
Wasif Khan et al. PLoS One 2023 18(12) e0293925
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Patterns of Morbidity Across the Lifespan: A Population Segmentation Framework for Classifying Health Care Needs for All Ages.
Klaus W Lemke et al. Med Care 2023
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Establishment of a model for predicting preterm birth based on the machine learning algorithm.
Yao Zhang et al. BMC Pregnancy Childbirth 2023 23(1) 779
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The Transformative Potential of AI in Obstetrics and Gynecology.
Kevin Dick et al. J Obstet Gynaecol Can 2023 102277
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Prevalence and course of pregnancy symptoms using self-reported pregnancy app symptom tracker data
M Nissen et al, NPJ Digital Medicine, October 11, 2023
Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity.
Neal G Ravindra et al. NPJ Digit Med 2023 6(1) 171
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An Interpretable Longitudinal Preeclampsia Risk Prediction Using Machine Learning.
Braden W Eberhard et al. medRxiv 2023
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Deep hybrid model for maternal health risk classification in pregnancy: synergy of ANN and random forest.
Taofeeq Oluwatosin Togunwa et al. Front Artif Intell 2023 61213436
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Development of machine learning models to predict gestational diabetes risk in the first half of pregnancy.
Gabriel Cubillos et al. BMC Pregnancy Childbirth 2023 23(1) 469
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Improving outcomes of Assisted Reproductive Technologies using Artificial Intelligence for Sperm Selection.
Nicole Lustgarten Guahmich et al. Fertil Steril 2023
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Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis.
Riccardo Rescinito et al. Healthcare (Basel) 2023 11(11)
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The role of artificial intelligence in hypertensive disorders of pregnancy: towards personalized healthcare.
Mohanad Alkhodari et al. Expert Rev Cardiovasc Ther 2023
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Using Machine Learning and Artificial Intelligence to Predict Diabetes Mellitus Among Women Population.
Ali Mamoon Alfalki et al. Curr Diabetes Rev 2023
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An ultrasound-based deep learning radiomic model combined with clinical data to predict clinical pregnancy after frozen embryo transfer: a pilot cohort study.
Xiaowen Liang et al. Reprod Biomed Online 2023
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Application and Progress of Artificial Intelligence in Fetal Ultrasound.
Sushan Xiao et al. J Clin Med 2023 12(9)
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Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.
Yequn Chen et al. Hypertens Res 2023
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Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes.
Huiqi Y Lu et al. IEEE reviews in biomedical engineering 2023 PP
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Preterm birth and maternal heart disease: A machine learning analysis using the Korean national health insurance database.
Jue Seong Lee et al. PloS one 2023 18(3) e0283959
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Big Data Analytics to Reduce Preventable Hospitalizations-Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions.
Timo Schulte et al. International journal of environmental research and public health 2023 20(6)
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A Comprehensive Review of the Role of Artificial Intelligence in Obstetrics and Gynecology.
Sagar N Malani et al. Cureus 2023 15(2) e34891
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Machine learning-based clinical decision support systems for pregnancy care: A systematic review.
Yuhan Du et al. International journal of medical informatics 2023 173105040
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 30, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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