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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 19, 2024
. (Total: 63627 Documents since 2012)
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Many Models, Little Adoption-What Accounts for Low Uptake of Machine Learning Models for Atrial Fibrillation Prediction and Detection?
Yuki Kawamura et al. J Clin Med 2024 13(5)
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Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study.
Richard M Yoo et al. JMIR Med Inform 2024 12e51171
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Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing.
Marta Fernandes et al. medRxiv 2024
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Machine Learning-Based Prediction of Stroke in Emergency Departments.
Vida Abedi et al. Ther Adv Neurol Disord 2024 1717562864241239108
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PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.
Giorgio Colangelo et al. Stroke 2024
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Development and Validation of Machine Learning Algorithms to Predict 1-Year Ischemic Stroke and Bleeding Events in Patients with Atrial Fibrillation and Cancer.
Bang Truong et al. Cardiovasc Toxicol 2024
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Emerging artificial intelligence-aided diagnosis and management methods for ischemic strokes and vascular occlusions: A comprehensive review.
G A U R I Parvathy et al. World Neurosurg X 2024 22100303
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Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data.
Jun-Bo Tu et al. Sci Rep 2024 14(1) 5245
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Analyzing prehospital delays in recurrent acute ischemic stroke: Insights from interpretable machine learning.
Youli Jiang et al. Patient Educ Couns 2024 123108228
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Machine learning based predictive model of Type 2 diabetes complications using Malaysian National Diabetes Registry: A study protocol.
Mohamad Zulfikrie Abas et al. J Public Health Res 2024 13(1) 22799036241231786
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Developmental Prediction of Poststroke Patients in Activities of Daily Living by Using Tree-Structured Parzen Estimator-Optimized Stacking Ensemble Approaches.
Pei-Hua Lin et al. IEEE J Biomed Health Inform 2024 PP
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A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes.
Yongkai Liu et al. AJNR Am J Neuroradiol 2024
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Large datasets from Electronic Health Records predict seizures after ischemic strokes: A Machine Learning approach.
Alain Lekoubou et al. medRxiv 2024
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FDA Review of Radiologic AI Algorithms: Process and Challenges.
Kuan Zhang et al. Radiology 2024 310(1) e230242
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Stroke classification and treatment support system artificial intelligence for usefulness of stroke diagnosis.
Nobukazu Miyamoto et al. Front Neurol 2023 141295642
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Predicting 90-day prognosis for patients with stroke: a machine learning approach.
Ahmad A Abujaber et al. Front Neurol 2023 141270767
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Detection of Cognitive Impairment From eSAGE Metadata Using Machine Learning.
Ryoma Kawakami et al. Alzheimer Dis Assoc Disord 2023
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A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study.
Kai Wang et al. Front Endocrinol (Lausanne) 2023 141165178
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A novel risk score predicting 30-day hospital re-admission of patients with acute stroke by machine learning model.
Giovanna Mercurio et al. Eur J Neurol 2023
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Predicting short-term outcomes in atrial-fibrillation-related stroke using machine learning.
Eun-Tae Jeon et al. Front Neurol 2023 141243700
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Interpretable Machine Learning-Based Predictive Modeling of Patient Outcomes Following Cardiac Surgery.
Adeel Abbasi et al. J Thorac Cardiovasc Surg 2023
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A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke.
Ting Fang et al. J Xray Sci Technol 2023
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Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.
Meraj Neyazi et al. Clin Chem Lab Med 2023
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Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study.
Rui Wen et al. Front Neurol 2023 141247492
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Machine learning applications in stroke medicine: advancements, challenges, and future prospectives.
Mario Daidone et al. Neural Regen Res 2023 19(4) 769-773
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[Establishment and evaluation of a predictive model for early neurological deterioration after intravenous thrombolysis in acute ischemic stroke based on machine learning].
Zhe Lyu et al. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue 2023 35(9) 945-950
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Predicting Major Adverse Cardiovascular Events Following Carotid Endarterectomy Using Machine Learning.
Ben Li et al. J Am Heart Assoc 2023 e030508
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Explainable Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Machine Learning Techniques in a Population of 1780 Patients.
Chien Wei Oei et al. Sensors (Basel) 2023 23(18)
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An artificial intelligence-based prognostic prediction model for hemorrhagic stroke.
Yihao Chen et al. Eur J Radiol 2023 167111081
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Using Neural Networks Algorithm in Ischemic Stroke Diagnosis: A Systematic Review.
Suebsarn Ruksakulpiwat et al. J Multidiscip Healthc 2023 162593-2602
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 19, 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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