Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Johannes, Fritsch"'
Autor:
Moein E. Samadi, Jorge Guzman-Maldonado, Kateryna Nikulina, Hedieh Mirzaieazar, Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Andreas Schuppert
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract The development of reliable mortality risk stratification models is an active research area in computational healthcare. Mortality risk stratification provides a standard to assist physicians in evaluating a patient’s condition or prognosi
Externí odkaz:
https://doaj.org/article/fb473d74a042418b9eb0ef2e1b859041
Autor:
Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Mina Iravani, Pejman Farhadi Ghalati, Sina Saffaran, Declan G. Bates, Jonathan G. Hardman, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 5, Pp 611-620 (2024)
Goal: Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their
Externí odkaz:
https://doaj.org/article/44befcf235114feabf6f4ed4938e85a4
Autor:
Kilian Merkelbach, Steffen Schaper, Christian Diedrich, Sebastian Johannes Fritsch, Andreas Schuppert
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-22 (2023)
Abstract Electronic health records (EHRs) are used in hospitals to store diagnoses, clinician notes, examinations, lab results, and interventions for each patient. Grouping patients into distinct subsets, for example, via clustering, may enable the d
Externí odkaz:
https://doaj.org/article/3550f0b03ca9446abf4a90082240f013
Speckle tracking ultrasonography as a new tool to assess diaphragmatic function: a feasibility study
Autor:
Sebastian Johannes Fritsch, Nima Hatam, Andreas Goetzenich, Gernot Marx, Rüdiger Autschbach, Leo Heunks, Johannes Bickenbach, Christian Simon Bruells
Publikováno v:
Ultrasonography, Vol 41, Iss 2, Pp 403-415 (2022)
A reliable method of measuring diaphragmatic function at the bedside is still lacking. Widely used two-dimensional (2D) ultrasonographic measurements, such as diaphragm excursion, diaphragm thickness, and fractional thickening (FT) have failed to sho
Externí odkaz:
https://doaj.org/article/c93b5bbe66fd401191f3b52149c19223
Autor:
Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Gernot Marx, Johannes Bickenbach, Andreas Schuppert
Publikováno v:
BMC Infectious Diseases, Vol 21, Iss 1, Pp 1-9 (2021)
Abstract Background The impact of biometric covariates on risk for adverse outcomes of COVID-19 disease was assessed by numerous observational studies on unstratified cohorts, which show great heterogeneity. However, multilevel evaluations to find po
Externí odkaz:
https://doaj.org/article/f8bfb3e4f47749f882cb6485eab04ac6
Autor:
Konstantin Sharafutdinov, Jayesh S. Bhat, Sebastian Johannes Fritsch, Kateryna Nikulina, Moein E. Samadi, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert
Publikováno v:
Frontiers in Big Data, Vol 5 (2022)
Machine learning (ML) models are developed on a learning dataset covering only a small part of the data of interest. If model predictions are accurate for the learning dataset but fail for unseen data then generalization error is considered high. Thi
Externí odkaz:
https://doaj.org/article/4c8c914b67c34e4eba51ceced1d34906
Autor:
Gernot Marx, Michael Dreher, Johannes Bickenbach, Sebastian Johannes Fritsch, Tim-Philipp Simon
Publikováno v:
BMJ Open Respiratory Research, Vol 9, Iss 1 (2022)
Externí odkaz:
https://doaj.org/article/422c55f0f7ca4ef4af3e2af83817565c
Autor:
Christian Stoppe, Ulf Peter Neumann, Gregory van der Kroft, Sebastian Johannes Johannes Fritsch, S S Rensen, Steffen Wigger, Andreas Lambertz, S W M Olde Damink, Christian S Bruells
Publikováno v:
BMJ Open, Vol 11, Iss 11 (2021)
Introduction Sarcopenia is associated with reduced pulmonary function in healthy adults, as well as with increased risk of pneumonia following abdominal surgery. Consequentially, postoperative pneumonia prolongs hospital admission, and increases in-h
Externí odkaz:
https://doaj.org/article/54f8259687fc4d638946b65a89251929
Autor:
Stefan Kluge, Christian Putensen, Danny Ammon, Silke Haferkamp, Saskia Deffge, Thomas Wendt, Daniel Tiller, André Scherag, Philipp Simon, Johannes Bickenbach, Sebastian Johannes Fritsch, Julian Benedict Kunze, Oliver Maassen, Jennifer Kistermann, Irina Lutz, Nora Kristiana Voellm, Volker Lowitsch, Richard Polzin, Konstantin Sharafutdinov, Hannah Mayer, Lars Kuepfer, Rolf Burghaus, Walter Schmitt, Joerg Lippert, Morris Riedel, Chadi Barakat, André Stollenwerk, Simon Fonck, Sven Zenker, Felix Erdfelder, Daniel Grigutsch, Rainer Kram, Susanne Beyer, Knut Kampe, Jan Erik Gewehr, Friederike Salman, Patrick Juers, Emilia Wisotzki, Sebastian Gross, Lorenz Homeister, Frank Bloos, Susanne Mueller, Julia Palm, Nora Jahn, Markus Loeffler, Tobias Schuerholz, Petra Groeber, Andreas Schuppert
Publikováno v:
BMJ Open, Vol 11, Iss 4 (2021)
Introduction The acute respiratory distress syndrome (ARDS) is a highly relevant entity in critical care with mortality rates of 40%. Despite extensive scientific efforts, outcome-relevant therapeutic measures are still insufficiently practised at th
Externí odkaz:
https://doaj.org/article/16921f71636846b9984cf353bd67fb35
Autor:
Konstantin Sharafutdinov, Sebastian Johannes Fritsch, Mina Iravani, Pejman Farhadi Ghalati, Sina Saffaran, Declan G. Bates, Jonathan G. Hardman, Richard Polzin, Hannah Mayer, Gernot Marx, Johannes Bickenbach, Andreas Schuppert
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology. :1-11
GoalMachine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40142132df982181b39ca2858c77240e
https://doi.org/10.1109/ojemb.2023.3243190
https://doi.org/10.1109/ojemb.2023.3243190