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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 25, 2024
. (Total: 63675 Documents since 2012)
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Unlocking new potential of clinical diagnosis with artificial intelligence: Finding new patterns of clinical and lab data.
Pradeep Kumar Dabla et al. World J Diabetes 2024 15(3) 308-310
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Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review protocol.
Joana Seringa et al. BMJ Open 2024 14(4) e083188
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Contemporary attitudes and beliefs on coronary artery calcium from social media using artificial intelligence.
Sulaiman Somani et al. NPJ Digit Med 2024 7(1) 83
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Major Depressive Disorder Prediction Based on Sleep-Wake Disorders Symptoms in US Adolescents: A Machine Learning Approach from National Sleep Research Resource.
Jingsong Luo et al. Psychol Res Behav Manag 2024 17691-703
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Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race.
Galvin Khara et al. Commun Med (Lond) 2024 4(1) 21
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Clinical Evaluation of Deep Learning for Tumor Delineation on F-FDG PET/CT of Head and Neck Cancer.
David G Kovacs et al. J Nucl Med 2024
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Consore: A Powerful Federated Data Mining Tool Driving a French Research Network to Accelerate Cancer Research.
Julien Guérin et al. Int J Environ Res Public Health 2024 21(2)
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An ecological examination of early adolescent e-cigarette use: A machine learning approach to understanding a health epidemic.
Alejandro L Vázquez et al. PLoS One 2024 19(2) e0287878
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Evaluating the clinical utility of artificial intelligence assistance and its explanation on the glioma grading task.
Weina Jin et al. Artif Intell Med 2024 148102751
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Are better AI algorithms for breast cancer detection also better at predicting risk? A paired case-control study.
Ruggiero Santeramo et al. Breast Cancer Res 2024 26(1) 25
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Automated Machine Learning for Predicting Diabetic Retinopathy Progression From Ultra-Widefield Retinal Images.
Paolo S Silva et al. JAMA Ophthalmol 2024
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Exploring the Value of MRI Measurement of Hippocampal Volume for Predicting the Occurrence and Progression of Alzheimer's Disease Based on Artificial Intelligence Deep Learning Technology and Evidence-Based Medicine Meta-Analysis.
Jianguo Zhou et al. J Alzheimers Dis 2024
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Image analysis-based machine learning for the diagnosis of retinopathy of prematurity: A meta-analysis and systematic review.
Yihang Chu et al. Ophthalmol Retina 2024
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Digital Technologies in Heart Failure Management.
Evrim Simsek et al. Turk Kardiyol Dern Ars 2024 52(1) 52-60
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Traumatic Brain Injury Rehabilitation Outcome Prediction Using Machine Learning Methods.
Nitin Nikamanth Appiah Balaji et al. Arch Rehabil Res Clin Transl 2024 5(4) 100295
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Real-world evaluation of smartphone-based artificial intelligence to screen for diabetic retinopathy in Dominica: a clinical validation study.
Oliver Kemp et al. BMJ Open Ophthalmol 2023 8(1)
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Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data.
Yonghan Cha et al. Medicina (Kaunas) 2023 59(12)
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Digital measurement of SARS-CoV-2 transmission risk from 7 million contacts.
Luca Ferretti et al. Nature 2023
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Air quality and cancer risk in the All of Us Research Program.
Andrew Craver et al. Cancer Causes Control 2023
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Applications of digital Medicine in oncology: Prospects and challenges.
Hewei Ge et al. Cancer Innov 2023 1(4) 285-292
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External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population.
Olasubomi J Omoleye et al. Radiol Artif Intell 2023 5(6) e220299
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Machine learning algorithms for the prognostication of abdominal aortic aneurysm progression: a systematic review.
Nazifa Ullah et al. Minerva Surg 2023
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Early prognostication of critical patients with spinal cord injury: A machine learning study with 1485 cases.
Guoxin Fan et al. Spine (Phila Pa 1976) 2023
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The value of standards for health datasets in artificial intelligence-based applications.
Anmol Arora et al. Nat Med 2023
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Machine Learning Improves the Accuracy of Trauma Team Activation Level Assignments in Pediatric Patients.
Catherine W Liu et al. J Pediatr Surg 2023
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Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review.
Hassan Mumtaz et al. Front Digit Health 2023 51203945
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Review: Machine learning in precision pharmacotherapy of type 2 diabetes-A promising future or a glimpse of hope?
Xiantong Zou et al. Digit Health 2023 920552076231203879
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An Actionable Expert-System Algorithm to Support Nurse-Led Cancer Survivorship Care: Algorithm Development Study.
Kaylen J Pfisterer et al. JMIR Cancer 2023 9e44332
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Predicting the drop out from the maternal, newborn and child healthcare continuum in three East African Community countries: application of machine learning models.
Chenai Mlandu et al. BMC Med Inform Decis Mak 2023 23(1) 191
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Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.
Jiping Wang et al. Yale J Biol Med 2023 96(3) 327-346
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 25, 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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