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Klaus Lemke

Showing results (1-10 of 7) with videos related to

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Health Affairs (Project Hope)|February 11, 2012
Adjusting for risk selection in state health insurance exchanges will be critically important and feasible, but not easyJonathan P Weiner, Erin Trish, Chad Abrams, et al.
The American Journal of Psychiatry|May 15, 2012
Risk adjustment in health insurance exchanges for individuals with mental illnessColleen L Barry, Jonathan P Weiner, Klaus Lemke, et al.
JMIR Formative Research|June 2, 2026
Improving models to predict care utilization using machine learning: a retrospective observational studyChristopher Kitchen, Talan Zhang, Klaus Lemke, et al.
JMIR Formative Research|June 26, 2026
Improving Models to Predict Care Utilization Using Machine Learning: Retrospective Observational StudyChristopher Kitchen, Talan Zhang, Klaus Lemke, et al.
Plos One|March 7, 2019
Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adultsHong J Kan, Hadi Kharrazi, Hsien-Yen Chang, et al.
JAMA Psychiatry|June 25, 2020
Predictive Modeling of Opioid Overdose Using Linked Statewide Medical and Criminal Justice DataBrendan Saloner, Hsien-Yen Chang, Noa Krawczyk, et al.
Medical Care|September 14, 2020
The Impact of Various Risk Assessment Time Frames on the Performance of Opioid Overdose Forecasting ModelsHsien-Yen Chang, Lindsey Ferris, Matthew Eisenberg, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Health Affairs (Project Hope)|February 11, 2012
Adjusting for risk selection in state health insurance exchanges will be critically important and feasible, but not easyJonathan P Weiner, Erin Trish, Chad Abrams, et al.
The American Journal of Psychiatry|May 15, 2012
Risk adjustment in health insurance exchanges for individuals with mental illnessColleen L Barry, Jonathan P Weiner, Klaus Lemke, et al.
JMIR Formative Research|June 2, 2026
Improving models to predict care utilization using machine learning: a retrospective observational studyChristopher Kitchen, Talan Zhang, Klaus Lemke, et al.
JMIR Formative Research|June 26, 2026
Improving Models to Predict Care Utilization Using Machine Learning: Retrospective Observational StudyChristopher Kitchen, Talan Zhang, Klaus Lemke, et al.
Plos One|March 7, 2019
Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adultsHong J Kan, Hadi Kharrazi, Hsien-Yen Chang, et al.
JAMA Psychiatry|June 25, 2020
Predictive Modeling of Opioid Overdose Using Linked Statewide Medical and Criminal Justice DataBrendan Saloner, Hsien-Yen Chang, Noa Krawczyk, et al.
Medical Care|September 14, 2020
The Impact of Various Risk Assessment Time Frames on the Performance of Opioid Overdose Forecasting ModelsHsien-Yen Chang, Lindsey Ferris, Matthew Eisenberg, et al.
Pageof 1