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Authors: Adesh Kadambi, BEng, Isabel Fulcher, PhD, Kartik Venkatesh, MD, PhD, Jonathan S. Schor, PhD, Mark A. Clapp, MD, MPH, Timothy Wen, MD, MPH
Journal: AJOG MFM
Key Findings: By applying machine learning to clinical risk factors and EHR system data available in the first trimester, we developed predictive models for GDM with satisfactory performance. Prediction models may provide a more optimal strategy to identify those who are at highest risk for GDM in future studies.
Paper
Authors: Adesh Kadambi, BEng, Isabel Fulcher, PhD, Kartik Venkatesh, MD, PhD, Jonathan S. Schor, PhD, Mark A. Clapp, MD, MPH, Timothy Wen, MD, MPH
Journal: AJOG MFM
Key Findings: By applying machine learning to clinical risk factors and EHR system data available in the first trimester, we developed predictive models for GDM with satisfactory performance. Prediction models may provide a more optimal strategy to identify those who are at highest risk for GDM in future studies.
Paper
Authors: Adesh Kadambi, BEng, Isabel Fulcher, PhD, Kartik Venkatesh, MD, PhD, Jonathan S. Schor, PhD, Mark A. Clapp, MD, MPH, Timothy Wen, MD, MPH
Journal: AJOG MFM
Key Findings: By applying machine learning to clinical risk factors and EHR system data available in the first trimester, we developed predictive models for GDM with satisfactory performance. Prediction models may provide a more optimal strategy to identify those who are at highest risk for GDM in future studies.
Paper
Authors: Adesh Kadambi, BEng, Isabel Fulcher, PhD, Kartik Venkatesh, MD, PhD, Jonathan S. Schor, PhD, Mark A. Clapp, MD, MPH, Timothy Wen, MD, MPH
Journal: AJOG MFM
Key Findings: By applying machine learning to clinical risk factors and EHR system data available in the first trimester, we developed predictive models for GDM with satisfactory performance. Prediction models may provide a more optimal strategy to identify those who are at highest risk for GDM in future studies.
Paper
Authors: Adesh Kadambi, BEng, Isabel Fulcher, PhD, Kartik Venkatesh, MD, PhD, Jonathan S. Schor, PhD, Mark A. Clapp, MD, MPH, Timothy Wen, MD, MPH
Journal: AJOG MFM
Key Findings: By applying machine learning to clinical risk factors and EHR system data available in the first trimester, we developed predictive models for GDM with satisfactory performance. Prediction models may provide a more optimal strategy to identify those who are at highest risk for GDM in future studies.
Paper
