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Precision Health Database


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Reproductive and Child Health

Last data update: Feb 07, 2023. (Total: 52530 Documents since 2012)
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Assessment of Retinopathy of Prematurity Regression and Reactivation Using an Artificial Intelligence-Based Vascular Severity Score.
Eilts Sonja K et al. JAMA network open 2023 6(1) e2251512
Artificial intelligence for the diagnosis of retinopathy of prematurity: A systematic review of current algorithms.
Ramanathan Ashwin et al. Eye (London, England) 2022
Evaluation of an Artificial Intelligence System for Retinopathy of Prematurity Screening in Nepal and Mongolia.
Cole Emily et al. Ophthalmology science 2022 2(4) 100165
Improved Training Efficiency for Retinopathy of Prematurity Deep Learning Models Using Comparison versus Class Labels.
Hanif Adam et al. Ophthalmology science 2022 2(2) 100122
External Validation of a Retinopathy of Prematurity Screening Model Using Artificial Intelligence in 3 Low- and Middle-Income Populations.
Coyner Aaron S et al. JAMA ophthalmology 2022
Early Diagnosis and Quantitative Analysis of Stages in Retinopathy of Prematurity Based on Deep Convolutional Neural Networks.
Li Peng et al. Translational vision science & technology 2022 11(5) 17
Predicting clinical outcomes using artificial intelligence and machine learning in neonatal intensive care units: a systematic review.
McAdams Ryan M et al. Journal of perinatology : official journal of the California Perinatal Association 2022
Comparison of Multivariable Logistic Regression and Machine Learning Models for Predicting Bronchopulmonary Dysplasia or Death in Very Preterm Infants.
Khurshid Faiza et al. Frontiers in pediatrics 2021 9759776
Developing practical clinical tools for predicting neonatal mortality at a neonatal intensive care unit in Tanzania.
Kovacs Dory et al. BMC pediatrics 2021 21(1) 537
Ethics of Artificial Intelligence in Medicine and Ophthalmology.
Abdullah Yasser Ibraheem et al. Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) 2021 10(3) 289-298
Evaluation of artificial intelligence-based quantitative analysis to identify clinically significant severe retinopathy of prematurity.
Li Jie et al. Retina (Philadelphia, Pa.) 2021
Machine Learning Assessment of Early Life Factors Predicting Suicide Attempt in Adolescence or Young Adulthood.
Navarro Marie C et al. JAMA network open 2021 4(3) e211450
Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.
Campbell J Peter et al. Pediatrics 2021
Current Application of Digital Diagnosing Systems for Retinopathy of Prematurity.
Bao Yuekun et al. Computer methods and programs in biomedicine 2020 Nov 105871
Diving Deep into Deep Learning: An Update on Artificial Intelligence in Retina.
Goldhagen Brian E et al. Current ophthalmology reports 2020 Sep 8(3) 121-128
Evaluation of a novel retinopathy of prematurity severity scale applied by clinicians and deep learning.
Campbell J Peter et al. Ophthalmology 2020 Oct
Artificial Intelligence in Retinopathy of Prematurity Diagnosis.
Scruggs Brittni A et al. Translational vision science & technology 2020 Feb 9(2) 5
Artificial intelligence for retinopathy of prematurity.
Gensure Rebekah H et al. Current opinion in ophthalmology 2020 Jul
Application of Artificial Intelligence in Targeting Retinal Diseases.
Sorrentino Francesco Saverio et al. Current drug targets 2020 Jul
Insights into the growing popularity of artificial intelligence in ophthalmology.
Dutt Sreetama et al. Indian journal of ophthalmology 2020 Jul 68(7) 1339-1346
Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes.
Burgos-Artizzu Xavier P et al. Scientific reports 2020 Jun 10(1) 10200
Real world variability in plus disease identified using a deep learning-based retinopathy of prematurity severity scale.
Choi Rene Y et al. Ophthalmology. Retina 2020 May
Evaluation of artificial intelligence-based telemedicine screening for retinopathy of prematurity.
Greenwald Miles F et al. Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus 2020 Apr
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging.
Li Matthew D et al. NPJ digital medicine 2020 348
Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy, Third Edition.
Horton Mark B et al. Telemedicine journal and e-health : the official journal of the American Telemedicine Association 2020 Mar
Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.
Coyner Aaron S et al. Ophthalmology. Retina 2019 3(5) 444-450
Machine learning models for identifying preterm infants at risk of cerebral hemorrhage.
Turova Varvara et al. PloS one 2020 15(1) e0227419
Deep Learning Predicts Extreme Preterm Birth from Electronic Health Records.
Gao Cheng et al. Journal of biomedical informatics 2019 Oct 103334
Automated diagnosis and quantitative analysis of plus disease in retinopathy of prematurity based on deep convolutional neural networks.
Mao Jianbo et al. Acta ophthalmologica 2019 Sep
Automated Algorithms and Retinopathy of Prematurity Treatment.
Good William V, et al. JAMA ophthalmology 2019 7 0.
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