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Precision Health Database


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Reproductive and Child Health

Last data update: Jun 07, 2023. (Total: 60112 Documents since 2012)
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Machine learning predictive modelling for identification of predictors of acute respiratory infection and diarrhoea in Uganda's rural and urban settings.
Rornald Muhumuza Kananura et al. PLOS global public health 2023 2(5) e0000430
Biochemical identification of prepubertal boys with Klinefelter syndrome by combined reproductive hormone profiling using machine learning.
Andre Madsen et al. Endocrine connections 2023
A hybrid artificial intelligence model leverages multi-centric clinical data to improve fetal heart rate pregnancy prediction across time-lapse systems.
A Duval et al. Human reproduction (Oxford, England) 2023
Associations of Preterm Birth with Dental and Gastrointestinal Diseases: Machine Learning Analysis Using National Health Insurance Data.
In-Seok Song et al. International journal of environmental research and public health 2023 20(3)
A Bayesian network model for prediction of low or failed fertilization in assisted reproductive technology based on a large clinical real-world data.
Tian Tian et al. Reproductive biology and endocrinology : RB&E 2023 21(1) 8
Development of a Model to Estimate the Optimal Number of Oocytes to Attempt to Fertilize During Assisted Reproductive Technology Treatment.
Correia Katharine F B et al. JAMA network open 2023 6(1) e2249395
The Future Is Coming: Artificial Intelligence in the Treatment of Infertility Could Improve Assisted Reproduction Outcomes-The Value of Regulatory Frameworks.
Medenica Sanja et al. Diagnostics (Basel, Switzerland) 2022 12(12)
Development of a Model Predicting the Outcome of In Vitro Fertilization Cycles by a Robust Decision Tree Method.
Fu Kaiyou et al. Frontiers in endocrinology 2022 13877518
Evaluation of oocyte maturity using artificial intelligence quantification of follicle volume biomarker by three-dimensional ultrasound.
Liang Xiaowen et al. Reproductive biomedicine online 2022
Comparison of predictive models for cumulative live birth rate after treatment with ART.
Bardet Léna et al. Reproductive biomedicine online 2022
The Impact of Wearable Technologies in Health Research: Scoping Review.
Huhn Sophie et al. JMIR mHealth and uHealth 2022 10(1) e34384
Machine learning algorithms for predicting undernutrition among under-five children in Ethiopia.
Bitew Fikrewold H et al. Public health nutrition 2021 1-29
Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review.
Chen Zhiyi et al. Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine 2021
A machine learning algorithm can optimize the day of trigger to improve in vitro fertilization outcomes.
Hariton Eduardo et al. Fertility and sterility 2021
Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective study.
Ueno Satoshi et al. Fertility and sterility 2021
Factors Associated with In Vitro Fertilization Live Birth Outcome: A Comparison of Different Classification Methods.
Amini Payam et al. International journal of fertility & sterility 2021 15(2) 128-134
Machine-learning algorithm incorporating capacitated sperm intracellular pH predicts conventional in vitro fertilization success in normospermic patients.
Gunderson Stephanie Jean et al. Fertility and sterility 2021 Jan
Evaluating predictive models in reproductive medicine.
Curchoe Carol Lynn et al. Fertility and sterility 2020 Nov 114(5) 921-926
Development of a Dynamic Diagnosis Grading System for Infertility Using Machine Learning.
Liao ShuJie et al. JAMA network open 2020 Nov 3(11) e2023654
Cohort profile: CROSS-TRACKS: a population-based open cohort across healthcare sectors in Denmark.
Riis Anders Hammerich et al. BMJ open 2020 Oct 10(10) e039996
Artificial intelligence in in vitro fertilization: a computer decision support system for day-to-day management of ovarian stimulation during in vitro fertilization.
Letterie Gerard et al. Fertility and sterility 2020 Oct
AI in the treatment of fertility: key considerations.
Swain Jason et al. Journal of assisted reproduction and genetics 2020 Sep
Machine learning vs. classic statistics for the prediction of IVF outcomes.
Barnett-Itzhaki Zohar et al. Journal of assisted reproduction and genetics 2020 Aug
Prediction of sperm extraction in non-obstructive azoospermia patients: a machine-learning perspective.
Zeadna A et al. Human reproduction (Oxford, England) 2020 Jun
MRI-Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study.
Li Yong'ai et al. Journal of magnetic resonance imaging : JMRI 2020 Feb
Ovarian torsion: developing a machine-learned algorithm for diagnosis.
Otjen Jeffrey P et al. Pediatric radiology 2020 Jan
Data mining polycystic ovary morphology in electronic medical record ultrasound reports.
Cheng Jay Jojo et al. Fertility research and practice 2019 513
Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction.
Hicks Steven A et al. Scientific reports 2019 Nov 9(1) 16770
Personalized prediction of live birth prior to the first in vitro fertilization treatment: a machine learning method.
Qiu Jiahui et al. Journal of translational medicine 2019 Sep 17(1) 317
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization.
Khosravi Pegah et al. NPJ digital medicine 2019 221
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