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Discussion on “Approval policies for modifications to machine learning‐based software as a medical device: A study of biocreep” by Jean Feng, Scott Emerson, and Noah Simon

Biometrics, 2021-03, Vol.77 (1), p.49-51

Rose, Sherri

2021

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Targeted Learning: Causal Inference for Observational and Experimental Data

1. Aufl., 2011

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Reflection on modern methods: when worlds collide—prediction, machine learning and causal inference

International journal of epidemiology, 2021-01, Vol.49 (6), p.2058-2064

2021

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Ethical Machine Learning in Healthcare

Annual review of biomedical data science, 2021-07, Vol.4, p.123

2021

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Implementation of G-Computation on a Simulated Data Set: Demonstration of a Causal Inference Technique

American journal of epidemiology, 2011-04, Vol.173 (7), p.731-738

2011

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Mortality Risk Score Prediction in an Elderly Population Using Machine Learning

American journal of epidemiology, 2013-03, Vol.177 (5), p.443-452

ROSE, Sherri

2013

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Intersections of machine learning and epidemiological methods for health services research

International journal of epidemiology, 2021-01, Vol.49 (6), p.1763-1770

Rose, Sherri

2021

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A Machine Learning Framework for Plan Payment Risk Adjustment

Health services research, 2016-12, Vol.51 (6), p.2358-2374

Rose, Sherri

2016

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Predicting posttraumatic stress disorder following a natural disaster

Journal of psychiatric research, 2018-01, Vol.96, p.15-22

2018

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Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis

BMJ open, 2023-02, Vol.13 (2), p.e065751-e065751

2023

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Effects of episode-based payment on health care spending and utilization: Evidence from perinatal care in Arkansas

Journal of health economics, 2018-09, Vol.61, p.47-62

2018

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Identifying undercompensated groups defined by multiple attributes in risk adjustment

BMJ health & care informatics, 2021-09, Vol.28 (1), p.e100414

2021

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Machine Learning for Prediction in Electronic Health Data

JAMA network open, 2018-08, Vol.1 (4), p.e181404-e181404

Rose, Sherri

2018

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Considerations for outcome‐dependent biased sampling in health databases

Statistics in medicine, 2019-09, Vol.38 (22), p.4213-4215

Rose, Sherri

2019

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Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending

Health services research, 2018-10, Vol.53 (5), p.3836-3854

Rose, Sherri

2018

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Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies

1st ed. 2018., 2018

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Public reporting of colonoscopy quality is associated with an increase in endoscopist adenoma detection rate

Gastrointestinal endoscopy, 2015-10, Vol.82 (4), p.676-682

2015

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Prediction of absolute risk of acute graft-versus-host disease following hematopoietic cell transplantation

PloS one, 2018-01, Vol.13 (1), p.e0190610-e0190610

2018

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The impact of exclusion criteria on a physician’s adenoma detection rate

Gastrointestinal endoscopy, 2015-10, Vol.82 (4), p.668-675

2015

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Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies

American journal of epidemiology, 2017-01, Vol.185 (1), p.65-73

2017

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Machine learning for causal inference in Biostatistics

Biostatistics (Oxford, England), 2020-04, Vol.21 (2), p.336-338

2020

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Conditional cross‐design synthesis estimators for generalizability in Medicaid

Biometrics, 2023-12, Vol.79 (4), p.3859-3872

2023

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A conversation with Elizabeth A. Stuart

Health services and outcomes research methodology, 2016-12, Vol.16 (4), p.177-186

Rose, Sherri

2016

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Association of Nondiscrimination Policies With Mental Health Among Gender Minority Individuals

JAMA psychiatry (Chicago, Ill.), 2020-09, Vol.77 (9), p.952

2020

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'Que cherchent-ils au Ciel?': Seeing with the Blind in Bruegel, Baudelaire and Maeterlinck

Dix-neuf : journal of the Society of Dix-Neuviémistes, 2018-04, Vol.22 (1-2), p.39-57

Rose, Sherri

2018

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Discussion on “Approval policies for modifications to machine learning‐based software as a medical device: A study of biocreep” by Jean Feng, Scott Emerson, and Noah Simon

Targeted Learning: Causal Inference for Observational and Experimental Data

Reflection on modern methods: when worlds collide—prediction, machine learning and causal inference

Ethical Machine Learning in Healthcare

Implementation of G-Computation on a Simulated Data Set: Demonstration of a Causal Inference Technique

Mortality Risk Score Prediction in an Elderly Population Using Machine Learning

Intersections of machine learning and epidemiological methods for health services research

A Machine Learning Framework for Plan Payment Risk Adjustment

Predicting posttraumatic stress disorder following a natural disaster

Measuring concordance of data sources used for infectious disease research in the USA: a retrospective data analysis

Effects of episode-based payment on health care spending and utilization: Evidence from perinatal care in Arkansas

Identifying undercompensated groups defined by multiple attributes in risk adjustment

Machine Learning for Prediction in Electronic Health Data

Considerations for outcome‐dependent biased sampling in health databases

Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending

Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies

Public reporting of colonoscopy quality is associated with an increase in endoscopist adenoma detection rate

Prediction of absolute risk of acute graft-versus-host disease following hematopoietic cell transplantation

The impact of exclusion criteria on a physician’s adenoma detection rate

Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies

Machine learning for causal inference in Biostatistics

Conditional cross‐design synthesis estimators for generalizability in Medicaid

A conversation with Elizabeth A. Stuart

Association of Nondiscrimination Policies With Mental Health Among Gender Minority Individuals

'Que cherchent-ils au Ciel?': Seeing with the Blind in Bruegel, Baudelaire and Maeterlinck

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