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Niklas Giesa

Showing results (1-10 of 15) with videos related to

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Artificial Intelligence in Medicine|May 19, 2026
GHOSTS: Validated generation of synthetic hospital time seriesRustam Zhumagambetov, Niklas Giesa, Sebastian D Boie, et al.
Studies in Health Technology and Informatics|May 17, 2025
GRU-D Characterizes Age-Specific Temporal Missingness in MIMIC-IVNiklas Giesa, Mert Akguel, Sebastian Daniel Boie, et al.
Studies in Health Technology and Informatics|May 23, 2026
Physicians' Perspectives on Predictive Uncertainty in Machine Learning ModelsNicolas Frey, Niklas Giesa, Louis Agha-Mir-Salim, et al.
Frontiers in Medicine|February 9, 2026
Multimodal data for predictive medicine: algorithmic fusion of clinical data in anesthesiology and intensive careSebastian Daniel Boie, Niklas Giesa, Maria Sekutowicz, et al.
Studies in Health Technology and Informatics|May 17, 2025
Coding Clinic: A Multidisciplinary Approach Supporting Early-Stage Medical Data Science ResearchElias Grünewald, Jon Barrenetxea, Niklas Giesa, et al.
Scientific Reports|December 26, 2025
Fusion of clinical magnet resonance images and electronic health records promotes multimodal predictions of postoperative deliriumNiklas Giesa, Andrea Dell'Orco, Michael Scheel, et al.
JMIR Medical Informatics|October 13, 2022
A Recurrent Neural Network Model for Predicting Activated Partial Thromboplastin Time After Treatment With Heparin: Retrospective StudySebastian Daniel Boie, Lilian Jo Engelhardt, Nicolas Coenen, et al.
Communications Medicine|November 28, 2024
Applying a transformer architecture to intraoperative temporal dynamics improves the prediction of postoperative deliriumNiklas Giesa, Maria Sekutowicz, Kerstin Rubarth, et al.
Studies in Health Technology and Informatics|August 8, 2025
Beyond the Circuit. Evaluating the Impact of Social Robots in Pediatric Healthcare: Systematic ReviewChristine Knoll, Niklas Giesa, Sarah B Blakeslee, et al.
PLOS Digital Health|August 14, 2024
Predicting postoperative delirium assessed by the Nursing Screening Delirium Scale in the recovery room for non-cardiac surgeries without craniotomy: A retrospective study using a machine learning approachNiklas Giesa, Stefan Haufe, Mario Menk, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Artificial Intelligence in Medicine|May 19, 2026
GHOSTS: Validated generation of synthetic hospital time seriesRustam Zhumagambetov, Niklas Giesa, Sebastian D Boie, et al.
Studies in Health Technology and Informatics|May 17, 2025
GRU-D Characterizes Age-Specific Temporal Missingness in MIMIC-IVNiklas Giesa, Mert Akguel, Sebastian Daniel Boie, et al.
Studies in Health Technology and Informatics|May 23, 2026
Physicians' Perspectives on Predictive Uncertainty in Machine Learning ModelsNicolas Frey, Niklas Giesa, Louis Agha-Mir-Salim, et al.
Frontiers in Medicine|February 9, 2026
Multimodal data for predictive medicine: algorithmic fusion of clinical data in anesthesiology and intensive careSebastian Daniel Boie, Niklas Giesa, Maria Sekutowicz, et al.
Studies in Health Technology and Informatics|May 17, 2025
Coding Clinic: A Multidisciplinary Approach Supporting Early-Stage Medical Data Science ResearchElias Grünewald, Jon Barrenetxea, Niklas Giesa, et al.
Scientific Reports|December 26, 2025
Fusion of clinical magnet resonance images and electronic health records promotes multimodal predictions of postoperative deliriumNiklas Giesa, Andrea Dell'Orco, Michael Scheel, et al.
JMIR Medical Informatics|October 13, 2022
A Recurrent Neural Network Model for Predicting Activated Partial Thromboplastin Time After Treatment With Heparin: Retrospective StudySebastian Daniel Boie, Lilian Jo Engelhardt, Nicolas Coenen, et al.
Communications Medicine|November 28, 2024
Applying a transformer architecture to intraoperative temporal dynamics improves the prediction of postoperative deliriumNiklas Giesa, Maria Sekutowicz, Kerstin Rubarth, et al.
Studies in Health Technology and Informatics|August 8, 2025
Beyond the Circuit. Evaluating the Impact of Social Robots in Pediatric Healthcare: Systematic ReviewChristine Knoll, Niklas Giesa, Sarah B Blakeslee, et al.
PLOS Digital Health|August 14, 2024
Predicting postoperative delirium assessed by the Nursing Screening Delirium Scale in the recovery room for non-cardiac surgeries without craniotomy: A retrospective study using a machine learning approachNiklas Giesa, Stefan Haufe, Mario Menk, et al.
Pageof 2