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Machine learning models to predict end-stage kidney disease in chronic kidney disease stage 4

BMC nephrology, 2023-12, Vol.24 (1), p.376-376, Article 376

2023

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High physical activity alleviates the adverse effect of higher sedentary time on the incidence of chronic kidney disease

Journal of cachexia, sarcopenia and muscle, 2023-02, Vol.14 (1), p.622-631

2023

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Joint Modeling of Social Determinants and Clinical Factors to Define Subphenotypes in Out-of-Hospital Cardiac Arrest Survival: Cluster Analysis

JMIR aging, 2023-12, Vol.6, p.e51844-e51844

2023

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Use of a Policy Tree Algorithm to Identify Maximal Treatment Effect of Crystalloid Therapy in a Cohort of Critically Ill Patients With Sepsis: FR-PO062

Journal of the American Society of Nephrology, 2022-11, Vol.33 (11S), p.342-342

2022

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IMPACT OF VACCINATION ON MAJOR ADVERSE CARDIOVASCULAR EVENTS AMONG PATIENTS WITH COVID-19

Journal of the American College of Cardiology, 2023-03, Vol.81 (8), p.1684-1684

2023

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Impact of Vaccination on Major Adverse Cardiovascular Events in Patients With COVID-19 Infection

Journal of the American College of Cardiology, 2023-03, Vol.81 (9), p.928-930

2023

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Prevalence and Severity of Pruritus in Patients on Maintenance Hemodialysis: PUB100

Journal of the American Society of Nephrology, 2021-10, Vol.32 (10S), p.795-795

2021

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Federated Learning in Health care Using Structured Medical Data

Advances in kidney disease and health (Online), 2023-01, Vol.30 (1), p.4-16

2023

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Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis

Critical care (London, England), 2024-05, Vol.28 (1), p.156-156, Article 156

2024

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Discovery of Type 2 Diabetes Trajectories from Electronic Health Records

Oh, Wonsuk

2020

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ProQuest

Using sequence clustering to identify clinically relevant subphenotypes in patients with COVID-19 admitted to the intensive care unit

Journal of the American Medical Informatics Association : JAMIA, 2022-01, Vol.29 (3), p.489-499

2022

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A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19

Artificial intelligence in medicine, 2024-02, Vol.148, p.102750-102750, Article 102750

2024

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A Computational Method for Learning Disease Trajectories From Partially Observable EHR Data

IEEE journal of biomedical and health informatics, 2021-07, Vol.25 (7), p.2476-2486

2021

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IEEE_Xplore

Machine Learning Models Uncover Subphenotypes of AKI With Unique Signatures That Associate With Differing Clinical Outcomes: TH-OR07

Journal of the American Society of Nephrology, 2022-11, Vol.33 (11S), p.3-3

2022

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Incremental Effect of Aging on Obesity-Related Incident Chronic Kidney Disease in the Korean General Population

Journal of the American Medical Directors Association, 2021-08, Vol.22 (8), p.1751-1756.e2

2021

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Discrepancy between predicted and measured exercise intensity for eliciting the maximal rate of lipid oxidation

Nutrition, metabolism, and cardiovascular diseases, 2023-11, Vol.33 (11), p.2189-2198

2023

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P3‐077: A Translational Research Strategy to Individualize Prediction of Long‐Term Cognitive Trajectory

Alzheimer's & dementia, 2016-07, Vol.12 (7S_Part_17), p.P847-P847

2016

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A TRANSLATIONAL RESEARCH STRATEGY TO INDIVIDUALIZE PREDICTION OF LONG-TERM COGNITIVE TRAJECTORY

Alzheimer's & dementia, 2016-07, Vol.12 (7), p.P847-P847

2016

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USING BIG DATA TO INDIVIDUALIZE PREDICTION OF LONG-TERM COGNITIVE TRAJECTORY

Alzheimer's & dementia, 2016-07, Vol.12 (7), p.P185-P186

2016

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O1‐06‐01: Using Big Data To Individualize Prediction Of Long‐Term Cognitive Trajectory

Alzheimer's & dementia, 2016-07, Vol.12 (7S_Part_4), p.P185-P186

2016

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Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes

Clinical journal of the American Society of Nephrology, 2023-06, Vol.18 (6), p.716-726

2023

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Personalized long-term prediction of cognitive function: Using sequential assessments to improve model performance

Journal of biomedical informatics, 2017-12, Vol.76, p.78-86

2017

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Feasibility Study of a Machine Learning Approach to Predict Dementia Progression

2015 International Conference on Healthcare Informatics, 2015, p.450-450

2015

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Divisive Hierarchical Clustering towards Identifying Clinically Significant Pre-Diabetes Subpopulations

AMIA ... Annual Symposium proceedings, 2014, Vol.2014, p.1815-1824

2014

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Estimating Disease Onset Time by Modeling Lab Result Trajectories via Bayes Networks

2017 IEEE International Conference on Healthcare Informatics (ICHI), 2017, Vol.2017, p.374-379

2017

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Machine learning models to predict end-stage kidney disease in chronic kidney disease stage 4

High physical activity alleviates the adverse effect of higher sedentary time on the incidence of chronic kidney disease

Joint Modeling of Social Determinants and Clinical Factors to Define Subphenotypes in Out-of-Hospital Cardiac Arrest Survival: Cluster Analysis

Use of a Policy Tree Algorithm to Identify Maximal Treatment Effect of Crystalloid Therapy in a Cohort of Critically Ill Patients With Sepsis: FR-PO062

IMPACT OF VACCINATION ON MAJOR ADVERSE CARDIOVASCULAR EVENTS AMONG PATIENTS WITH COVID-19

Impact of Vaccination on Major Adverse Cardiovascular Events in Patients With COVID-19 Infection

Prevalence and Severity of Pruritus in Patients on Maintenance Hemodialysis: PUB100

Federated Learning in Health care Using Structured Medical Data

Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis

Discovery of Type 2 Diabetes Trajectories from Electronic Health Records

Using sequence clustering to identify clinically relevant subphenotypes in patients with COVID-19 admitted to the intensive care unit

A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19

A Computational Method for Learning Disease Trajectories From Partially Observable EHR Data

Machine Learning Models Uncover Subphenotypes of AKI With Unique Signatures That Associate With Differing Clinical Outcomes: TH-OR07

Incremental Effect of Aging on Obesity-Related Incident Chronic Kidney Disease in the Korean General Population

Discrepancy between predicted and measured exercise intensity for eliciting the maximal rate of lipid oxidation

P3‐077: A Translational Research Strategy to Individualize Prediction of Long‐Term Cognitive Trajectory

A TRANSLATIONAL RESEARCH STRATEGY TO INDIVIDUALIZE PREDICTION OF LONG-TERM COGNITIVE TRAJECTORY

USING BIG DATA TO INDIVIDUALIZE PREDICTION OF LONG-TERM COGNITIVE TRAJECTORY

O1‐06‐01: Using Big Data To Individualize Prediction Of Long‐Term Cognitive Trajectory

Joint Modeling of Clinical and Biomarker Data in Acute Kidney Injury Defines Unique Subphenotypes with Differing Outcomes

Personalized long-term prediction of cognitive function: Using sequential assessments to improve model performance

Feasibility Study of a Machine Learning Approach to Predict Dementia Progression

Divisive Hierarchical Clustering towards Identifying Clinically Significant Pre-Diabetes Subpopulations

Estimating Disease Onset Time by Modeling Lab Result Trajectories via Bayes Networks

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