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Prostate-Specific Antigen Kinetics During Follow-Up Are an Unreliable Trigger for Intervention in a Prostate Cancer Surveillance Program

Journal of clinical oncology, 2010-06, Vol.28 (17), p.2810-2816

2010

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PSA Doubling Time Versus PSA Velocity to Predict High-Risk Prostate Cancer: Data from the Baltimore Longitudinal Study of Aging

European urology, 2008-11, Vol.54 (5), p.1073-1080

2008

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Informatics in Medical Product Regulation: The Right Drug at the Right Dose for the Right Patient

Methods in molecular biology (Clifton, N.J.), 2022, Vol.2486, p.277

2022

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Interpretation of the prostate‐specific antigen history in assessing life‐threatening prostate cancer

BJU international, 2010-11, Vol.106 (9), p.1284-1292

2010

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Statistical methods for handling missing data to align with treatment policy strategy

Pharmaceutical statistics : the journal of the pharmaceutical industry, 2023-07, Vol.22 (4), p.650-670

2023

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Expectant Management of Prostate Cancer With Curative Intent: An Update of The Johns Hopkins Experience

The Journal of urology, 2007-12, Vol.178 (6), p.2359-2365

2007

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Biomarkers of exposure among U.S. cigar smokers: an analysis of 1999-2012 National Health and Nutrition Examination Survey (NHANES) data

Cancer epidemiology, biomarkers & prevention, 2014-12, Vol.23 (12), p.2906-2915

2014

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Considerations to address missing data when deriving clinical trial endpoints from digital health technologies

Contemporary clinical trials, 2022-02, Vol.113, p.106661-106661, Article 106661

2022

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Prostate Volume Changes Over Time: Results From the Baltimore Longitudinal Study of Aging

The Journal of urology, 2009-10, Vol.182 (4), p.1458-1462

2009

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Endpoints in diabetes cardiovascular outcome trials

The Lancet (British edition), 2018-06, Vol.391 (10138), p.2412-2412

2018

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Detection of Life-Threatening Prostate Cancer With Prostate-Specific Antigen Velocity During a Window of Curability

JNCI : Journal of the National Cancer Institute, 2006-11, Vol.98 (21), p.1521-1527

2006

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Accuracy of PCA3 Measurement in Predicting Short-Term Biopsy Progression in an Active Surveillance Program

The Journal of urology, 2010-02, Vol.183 (2), p.534-538

2010

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USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN THE TREATMENT OF PRESERVED CARDIAC FUNCTION HEART FAILURE WITH AN ALDOSTERONE ANTAGONIST TRIAL (TOPCAT)

Journal of the American College of Cardiology, 2020-03, Vol.75 (11), p.1028-1028

2020

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USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN PREVENTION OF EVENTS WITH ANGIOTENSIN-CONVERTING ENZYME INHIBITION (PEACE) TRIAL

Journal of the American College of Cardiology, 2020-03, Vol.75 (11), p.946-946

2020

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USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN THE SYSTOLIC BLOOD PRESSURE INTERVENTION TRIAL (SPRINT)

Journal of the American College of Cardiology, 2020-03, Vol.75 (11), p.2061-2061

2020

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Serum testosterone is associated with aggressive prostate cancer in older men: results from the Baltimore Longitudinal Study of Aging

BJU international, 2010-03, Vol.105 (6), p.824-829

2010

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Cigarette Smokers’ Use of Unconventional Tobacco Products and Associations With Quitting Activity: Findings From the ITC-4 U.S. Cohort

Nicotine & tobacco research, 2014-06, Vol.16 (6), p.672-681

2014

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IDENTIFYING PREDICTORS OF HOSPITALIZATION DUE TO HEART FAILURE IN THE TOPCAT TRIAL USING MACHINE LEARNING TECHNIQUES

Journal of the American College of Cardiology, 2019-03, Vol.73 (9), p.992-992

2019

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PREDICTORS OF ALL-CAUSE MORTALITY IN THE AIM-HIGH TRIAL IDENTIFIED BY MACHINE LEARNING

Journal of the American College of Cardiology, 2019-03, Vol.73 (9), p.1874-1874

2019

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PREDICTORS OF ALL-CAUSE MORTALITY IN THE SPRINT TRIAL IDENTIFIED BY MACHINE LEARNING

Journal of the American College of Cardiology, 2019-03, Vol.73 (9), p.1891-1891

2019

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PREDICTORS OF ALL-CAUSE MORTALITY IN THE BARI 2D TRIAL IDENTIFIED BY MACHINE-LEARNING

Journal of the American College of Cardiology, 2019-03, Vol.73 (9), p.280-280

2019

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Abstract 17059: Re-Use of Clinical Trial Data From the NHLBI Data Repository (BioLINCC) for Patient-Level Meta-Analyses of Cardiovascular Outcomes: Challenges and Opportunities

Circulation (New York, N.Y.), 2018-11, Vol.138 (Suppl_1 Suppl 1), p.A17059-A17059

2018

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Abstract 17121: Predictors of Death and Major Adverse Cardiovascular Events in the ACCORD Trial Identified by Random Survival Forest Based Machine-Learning

Circulation (New York, N.Y.), 2018-11, Vol.138 (Suppl_1 Suppl 1), p.A17121-A17121

2018

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Prostate Specific Antigen Testing Among the Elderly—When To Stop?

The Journal of urology, 2009-04, Vol.181 (4), p.1606-1614

2009

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Prostate-Specific Antigen Velocity Risk Count Assessment: A New Concept for Detection of Life-Threatening Prostate Cancer During Window of Curability

Urology (Ridgewood, N.J.), 2007-10, Vol.70 (4), p.685-690

2007

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Prostate-Specific Antigen Kinetics During Follow-Up Are an Unreliable Trigger for Intervention in a Prostate Cancer Surveillance Program

PSA Doubling Time Versus PSA Velocity to Predict High-Risk Prostate Cancer: Data from the Baltimore Longitudinal Study of Aging

Informatics in Medical Product Regulation: The Right Drug at the Right Dose for the Right Patient

Interpretation of the prostate‐specific antigen history in assessing life‐threatening prostate cancer

Statistical methods for handling missing data to align with treatment policy strategy

Expectant Management of Prostate Cancer With Curative Intent: An Update of The Johns Hopkins Experience

Biomarkers of exposure among U.S. cigar smokers: an analysis of 1999-2012 National Health and Nutrition Examination Survey (NHANES) data

Considerations to address missing data when deriving clinical trial endpoints from digital health technologies

Prostate Volume Changes Over Time: Results From the Baltimore Longitudinal Study of Aging

Endpoints in diabetes cardiovascular outcome trials

Detection of Life-Threatening Prostate Cancer With Prostate-Specific Antigen Velocity During a Window of Curability

Accuracy of PCA3 Measurement in Predicting Short-Term Biopsy Progression in an Active Surveillance Program

USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN THE TREATMENT OF PRESERVED CARDIAC FUNCTION HEART FAILURE WITH AN ALDOSTERONE ANTAGONIST TRIAL (TOPCAT)

USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN PREVENTION OF EVENTS WITH ANGIOTENSIN-CONVERTING ENZYME INHIBITION (PEACE) TRIAL

USE OF MACHINE LEARNING METHODOLOGY TO FIND PREDICTORS OF ALL-CAUSE MORTALITY IN THE SYSTOLIC BLOOD PRESSURE INTERVENTION TRIAL (SPRINT)

Serum testosterone is associated with aggressive prostate cancer in older men: results from the Baltimore Longitudinal Study of Aging

Cigarette Smokers’ Use of Unconventional Tobacco Products and Associations With Quitting Activity: Findings From the ITC-4 U.S. Cohort

IDENTIFYING PREDICTORS OF HOSPITALIZATION DUE TO HEART FAILURE IN THE TOPCAT TRIAL USING MACHINE LEARNING TECHNIQUES

PREDICTORS OF ALL-CAUSE MORTALITY IN THE AIM-HIGH TRIAL IDENTIFIED BY MACHINE LEARNING

PREDICTORS OF ALL-CAUSE MORTALITY IN THE SPRINT TRIAL IDENTIFIED BY MACHINE LEARNING

PREDICTORS OF ALL-CAUSE MORTALITY IN THE BARI 2D TRIAL IDENTIFIED BY MACHINE-LEARNING

Abstract 17059: Re-Use of Clinical Trial Data From the NHLBI Data Repository (BioLINCC) for Patient-Level Meta-Analyses of Cardiovascular Outcomes: Challenges and Opportunities

Abstract 17121: Predictors of Death and Major Adverse Cardiovascular Events in the ACCORD Trial Identified by Random Survival Forest Based Machine-Learning

Prostate Specific Antigen Testing Among the Elderly—When To Stop?

Prostate-Specific Antigen Velocity Risk Count Assessment: A New Concept for Detection of Life-Threatening Prostate Cancer During Window of Curability

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