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Markus Wolfien

Showing results (51-60 of 64) with videos related to

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Frontiers in Nutrition|December 27, 2024
Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as additional parametersKaren Rischmüller, Vanessa Caton, Markus Wolfien, et al.
Frontiers in Medicine|June 21, 2024
Streamlining intersectoral provision of real-world health data: a service platform for improved clinical research and patient careKatja Hoffmann, Igor Nesterow, Yuan Peng, et al.
European Journal of Nuclear Medicine and Molecular Imaging|July 29, 2025
[<sup>68</sup>Ga]Ga-NODAGA-RGD post MI reflects activated fibroblasts rather than angiogenesisMatti Raitza, Markus Wolfien, Heiko Lemcke, et al.
Studies in Health Technology and Informatics|September 3, 2025
GeMTeX's De-Identification in Action: Lessons Learned & Devil's DetailsChristina Lohr, Jakob Faller, Andrea Riedel, et al.
NPJ Digital Medicine|March 21, 2024
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligenceJan-Niklas Eckardt, Waldemar Hahn, Christoph Röllig, et al.
Ebiomedicine|August 8, 2017
Cardiac Function Improvement and Bone Marrow Response -: Outcome Analysis of the Randomized PERFECT Phase III Clinical Trial of Intramyocardial CD133<sup>+</sup> Application After Myocardial InfarctionGustav Steinhoff, Julia Nesteruk, Markus Wolfien, et al.
Nucleic Acids Research|June 6, 2017
The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in GalaxyBjörn A Grüning, Jörg Fallmann, Dilmurat Yusuf, et al.
Hemasphere|May 8, 2025
Age-stratified machine learning identifies divergent prognostic significance of molecular alterations in AMLJan-Niklas Eckardt, Waldemar Hahn, Rhonda E Ries, et al.
Orphanet Journal of Rare Diseases|August 14, 2024
How to customize common data models for rare diseases: an OMOP-based implementation and lessons learnedNajia Ahmadi, Michele Zoch, Oya Guengoeze, et al.
Ebiomedicine|July 7, 2020
Hematopoietic stem-cell senescence and myocardial repair - Coronary artery disease genotype/phenotype analysis of post-MI myocardial regeneration response induced by CABG/CD133+ bone marrow hematopoietic stem cell treatment in RCT PERFECT Phase 3Markus Wolfien, Denise Klatt, Amankeldi A Salybekov, et al.
Pageof 7

Showing results (51-60 of 64) with videos related to

Sort By:
Pageof 7
Frontiers in Nutrition|December 27, 2024
Identification of key factors for malnutrition diagnosis in chronic gastrointestinal diseases using machine learning underscores the importance of GLIM criteria as well as additional parametersKaren Rischmüller, Vanessa Caton, Markus Wolfien, et al.
Frontiers in Medicine|June 21, 2024
Streamlining intersectoral provision of real-world health data: a service platform for improved clinical research and patient careKatja Hoffmann, Igor Nesterow, Yuan Peng, et al.
European Journal of Nuclear Medicine and Molecular Imaging|July 29, 2025
[<sup>68</sup>Ga]Ga-NODAGA-RGD post MI reflects activated fibroblasts rather than angiogenesisMatti Raitza, Markus Wolfien, Heiko Lemcke, et al.
Studies in Health Technology and Informatics|September 3, 2025
GeMTeX's De-Identification in Action: Lessons Learned & Devil's DetailsChristina Lohr, Jakob Faller, Andrea Riedel, et al.
NPJ Digital Medicine|March 21, 2024
Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligenceJan-Niklas Eckardt, Waldemar Hahn, Christoph Röllig, et al.
Ebiomedicine|August 8, 2017
Cardiac Function Improvement and Bone Marrow Response -: Outcome Analysis of the Randomized PERFECT Phase III Clinical Trial of Intramyocardial CD133<sup>+</sup> Application After Myocardial InfarctionGustav Steinhoff, Julia Nesteruk, Markus Wolfien, et al.
Nucleic Acids Research|June 6, 2017
The RNA workbench: best practices for RNA and high-throughput sequencing bioinformatics in GalaxyBjörn A Grüning, Jörg Fallmann, Dilmurat Yusuf, et al.
Hemasphere|May 8, 2025
Age-stratified machine learning identifies divergent prognostic significance of molecular alterations in AMLJan-Niklas Eckardt, Waldemar Hahn, Rhonda E Ries, et al.
Orphanet Journal of Rare Diseases|August 14, 2024
How to customize common data models for rare diseases: an OMOP-based implementation and lessons learnedNajia Ahmadi, Michele Zoch, Oya Guengoeze, et al.
Ebiomedicine|July 7, 2020
Hematopoietic stem-cell senescence and myocardial repair - Coronary artery disease genotype/phenotype analysis of post-MI myocardial regeneration response induced by CABG/CD133+ bone marrow hematopoietic stem cell treatment in RCT PERFECT Phase 3Markus Wolfien, Denise Klatt, Amankeldi A Salybekov, et al.
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