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Erina Ghosh

Showing results (11-20 of 23) with videos related to

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Mayo Clinic Proceedings|May 6, 2019
Automated Continuous Acute Kidney Injury Prediction and Surveillance: A Random Forest ModelCaitlyn Chiofolo, Nicolas Chbat, Erina Ghosh, et al.
Journal of Visualized Experiments : Jove|September 17, 2014
Quantification of global diastolic function by kinematic modeling-based analysis of transmitral flow via the parametrized diastolic filling formalismSina Mossahebi, Simeng Zhu, Howard Chen, et al.
Clinical Kidney Journal|May 7, 2021
Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learningKhaled Shawwa, Erina Ghosh, Stephanie Lanius, et al.
Journal of Critical Care|February 12, 2023
Accurate and interpretable prediction of ICU-acquired AKIEmma Schwager, Erina Ghosh, Larry Eshelman, et al.
Journal of the Intensive Care Society|August 27, 2019
Descriptive study of differences in acute kidney injury progression patterns in General and Cardiac Intensive Care UnitsMarcin A Pachucki, Erina Ghosh, Larry Eshelman, et al.
American Journal of Nephrology|September 27, 2021
Estimation of Baseline Serum Creatinine with Machine LearningErina Ghosh, Larry Eshelman, Stephanie Lanius, et al.
Journal of Critical Care|January 28, 2021
Including urinary output to define AKI enhances the performance of machine learning models to predict AKI at admissionEmma Schwager, Stephanie Lanius, Erina Ghosh, et al.
Annals of Intensive Care|February 22, 2023
Association of systolic, diastolic, mean, and pulse pressure with morbidity and mortality in septic ICU patients: a nationwide observational studyAshish K Khanna, Takahiro Kinoshita, Annamalai Natarajan, et al.
Critical Care (London, England)|November 24, 2020
Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational studyChristopher Bourdeaux, Erina Ghosh, Louis Atallah, et al.
Frontiers in Medicine|January 5, 2024
Machine learning-based clinical decision support for infection risk predictionTing Feng, David P Noren, Chaitanya Kulkarni, et al.
Pageof 3

Showing results (11-20 of 23) with videos related to

Sort By:
Pageof 3
Mayo Clinic Proceedings|May 6, 2019
Automated Continuous Acute Kidney Injury Prediction and Surveillance: A Random Forest ModelCaitlyn Chiofolo, Nicolas Chbat, Erina Ghosh, et al.
Journal of Visualized Experiments : Jove|September 17, 2014
Quantification of global diastolic function by kinematic modeling-based analysis of transmitral flow via the parametrized diastolic filling formalismSina Mossahebi, Simeng Zhu, Howard Chen, et al.
Clinical Kidney Journal|May 7, 2021
Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learningKhaled Shawwa, Erina Ghosh, Stephanie Lanius, et al.
Journal of Critical Care|February 12, 2023
Accurate and interpretable prediction of ICU-acquired AKIEmma Schwager, Erina Ghosh, Larry Eshelman, et al.
Journal of the Intensive Care Society|August 27, 2019
Descriptive study of differences in acute kidney injury progression patterns in General and Cardiac Intensive Care UnitsMarcin A Pachucki, Erina Ghosh, Larry Eshelman, et al.
American Journal of Nephrology|September 27, 2021
Estimation of Baseline Serum Creatinine with Machine LearningErina Ghosh, Larry Eshelman, Stephanie Lanius, et al.
Journal of Critical Care|January 28, 2021
Including urinary output to define AKI enhances the performance of machine learning models to predict AKI at admissionEmma Schwager, Stephanie Lanius, Erina Ghosh, et al.
Annals of Intensive Care|February 22, 2023
Association of systolic, diastolic, mean, and pulse pressure with morbidity and mortality in septic ICU patients: a nationwide observational studyAshish K Khanna, Takahiro Kinoshita, Annamalai Natarajan, et al.
Critical Care (London, England)|November 24, 2020
Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational studyChristopher Bourdeaux, Erina Ghosh, Louis Atallah, et al.
Frontiers in Medicine|January 5, 2024
Machine learning-based clinical decision support for infection risk predictionTing Feng, David P Noren, Chaitanya Kulkarni, et al.
Pageof 3