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Diether Kramer

Showing results (11-20 of 42) with videos related to

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Studies in Health Technology and Informatics|June 25, 2020
Multivariable Risk Prediction of Dysphagia in Hospitalized Patients Using Machine LearningAnna Maria Lienhart, Diether Kramer, Stefanie Jauk, et al.
BMC Emergency Medicine|December 11, 2025
Negative predictive value of S100B in all types of traumatic brain injury in different aging groupsClemens Clar, Paul Puchwein, Diether Kramer, et al.
IEEE Journal of Biomedical and Health Informatics|June 22, 2023
A Transformer-Based Model Trained on Large Scale Claims Data for Prediction of Severe COVID-19 Disease ProgressionManuel Lentzen, Thomas Linden, Sai Veeranki, et al.
Studies in Health Technology and Informatics|August 24, 2019
Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical PracticeStefanie Jauk, Diether Kramer, Günther Stark, et al.
Studies in Health Technology and Informatics|July 4, 2018
On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine CareSai Veeranki, Dieter Hayn, Alphons Eggerth, et al.
Studies in Health Technology and Informatics|May 17, 2017
Development and Validation of a Multivariable Prediction Model for the Occurrence of Delirium in Hospitalized Gerontopsychiatry and Internal Medicine PatientsDiether Kramer, Sai Veeranki, Dieter Hayn, et al.
JAMIA Open|September 19, 2024
Machine learning-based delirium prediction in surgical in-patients: a prospective validation studyStefanie Jauk, Diether Kramer, Stefan Sumerauer, et al.
Archives of Orthopaedic and Trauma Surgery|June 30, 2026
Computed tomography findings in 11,504 adult patients with traumatic brain injury: a large real-world cohort study with a S100B subgroup analysisClemens Clar, Paul Puchwein, Maximilian Moshammer, et al.
Studies in Health Technology and Informatics|May 9, 2021
Machine Learning Based Risk Prediction for Major Adverse Cardiovascular EventsMichael Schrempf, Diether Kramer, Stefanie Jauk, et al.
Studies in Health Technology and Informatics|April 24, 2025
A Machine Learning-Based Risk Assessment Model for Poor Postoperative Pain OutcomeClaudia Kagerer, Stefanie Jauk, Diether Kramer, et al.
Pageof 5

Showing results (11-20 of 42) with videos related to

Sort By:
Pageof 5
Studies in Health Technology and Informatics|June 25, 2020
Multivariable Risk Prediction of Dysphagia in Hospitalized Patients Using Machine LearningAnna Maria Lienhart, Diether Kramer, Stefanie Jauk, et al.
BMC Emergency Medicine|December 11, 2025
Negative predictive value of S100B in all types of traumatic brain injury in different aging groupsClemens Clar, Paul Puchwein, Diether Kramer, et al.
IEEE Journal of Biomedical and Health Informatics|June 22, 2023
A Transformer-Based Model Trained on Large Scale Claims Data for Prediction of Severe COVID-19 Disease ProgressionManuel Lentzen, Thomas Linden, Sai Veeranki, et al.
Studies in Health Technology and Informatics|August 24, 2019
Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical PracticeStefanie Jauk, Diether Kramer, Günther Stark, et al.
Studies in Health Technology and Informatics|July 4, 2018
On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine CareSai Veeranki, Dieter Hayn, Alphons Eggerth, et al.
Studies in Health Technology and Informatics|May 17, 2017
Development and Validation of a Multivariable Prediction Model for the Occurrence of Delirium in Hospitalized Gerontopsychiatry and Internal Medicine PatientsDiether Kramer, Sai Veeranki, Dieter Hayn, et al.
JAMIA Open|September 19, 2024
Machine learning-based delirium prediction in surgical in-patients: a prospective validation studyStefanie Jauk, Diether Kramer, Stefan Sumerauer, et al.
Archives of Orthopaedic and Trauma Surgery|June 30, 2026
Computed tomography findings in 11,504 adult patients with traumatic brain injury: a large real-world cohort study with a S100B subgroup analysisClemens Clar, Paul Puchwein, Maximilian Moshammer, et al.
Studies in Health Technology and Informatics|May 9, 2021
Machine Learning Based Risk Prediction for Major Adverse Cardiovascular EventsMichael Schrempf, Diether Kramer, Stefanie Jauk, et al.
Studies in Health Technology and Informatics|April 24, 2025
A Machine Learning-Based Risk Assessment Model for Poor Postoperative Pain OutcomeClaudia Kagerer, Stefanie Jauk, Diether Kramer, et al.
Pageof 5