Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Matthias Schulte‐Althoff"'
Publikováno v:
Clinical and Translational Science, Vol 17, Iss 7, Pp n/a-n/a (2024)
Abstract Real‐world evidence (RWE) trials have a key advantage over conventional randomized controlled trials (RCTs) due to their potentially better generalizability. High generalizability of study results facilitates new biological insights and en
Externí odkaz:
https://doaj.org/article/4a1453900f614a248a7d9fb8863daa42
Autor:
Anatol-Fiete Näher, Matthias Schulte-Althoff, Marvin Kopka, Felix Balzer, Francisco Pozo-Martin
Publikováno v:
JMIR Public Health and Surveillance, Vol 10, p e49307 (2024)
BackgroundThe question of the utility of face masks in preventing acute respiratory infections has received renewed attention during the COVID-19 pandemic. However, given the inconclusive evidence from existing randomized controlled trials, evidence
Externí odkaz:
https://doaj.org/article/195e9dccb3724214875b3889a9c0a095
Autor:
Kathrin Seibert, Dominik Domhoff, Dominik Bruch, Matthias Schulte-Althoff, Daniel Fürstenau, Felix Biessmann, Karin Wolf-Ostermann
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 11, p e26522 (2021)
BackgroundArtificial intelligence (AI) holds the promise of supporting nurses’ clinical decision-making in complex care situations or conducting tasks that are remote from direct patient interaction, such as documentation processes. There has been
Externí odkaz:
https://doaj.org/article/58d79785d98247dd8995d10161fdd66e
Autor:
Anatol Fiete Näher, Matthias Schulte-Althoff, Marvin Kopka, Felix Balzer, Francisco Pozo-Martin
BACKGROUND The question of the utility of face masks in preventing acute respiratory infections has received renewed attention in the context of the COVID-19 pandemic. However, given the inconclusive evidence of existing RCT, evidence based on real-w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8465e22a73210a1b1c8a2897d745aa59
https://doi.org/10.2196/preprints.49307
https://doi.org/10.2196/preprints.49307
Autor:
Kathrin Seibert, Dominik Domhoff, Daniel Fürstenau, Felix Biessmann, Matthias Schulte-Althoff, Karin Wolf-Ostermann
Publikováno v:
BMC Digital Health. 1
Background and aim While artificial intelligence (AI) is being adapted for various life domains and applications related to medicine and healthcare, the use of AI in nursing practice is still scarce. The German Ministry for Education and Research fun
Publikováno v:
Information Systems Research.
The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growt
Autor:
Kathrin Seibert, Dominik Domhoff, Daniel Fürstenau, Felix Biessmann, Matthias Schulte-Althoff, Karin Wolf-Ostermann
Background and aim: While artificial intelligence (AI) is being adapted for various life domains and applications related to medicine and healthcare, the use of AI in nursing practice is still scarce. The German Ministry for Education and Research fu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::172509c8461d36a741eff6078c2205b0
https://doi.org/10.21203/rs.3.rs-2397771/v1
https://doi.org/10.21203/rs.3.rs-2397771/v1
Autor:
Sven, Rehfeld, Matthias, Schulte-Althoff, Fabian, Schreiber, Daniel, Fürstenau, Anatol-Fiete, Näher, Armin, Hauss, Charlotte, Köhler, Felix, Balzer
Publikováno v:
Studies in health technology and informatics. 294
Standardized fall risk scores have not proven to reliably predict falls in clinical settings. Machine Learning offers the potential to increase the accuracy of such predictions, possibly vastly improving care for patients at high fall risks. We devel
Autor:
Sven Rehfeld, Matthias Schulte-Althoff, Fabian Schreiber, Daniel Fürstenau, Anatol-Fiete Näher, Armin Hauss, Charlotte Köhler, Felix Balzer
Standardized fall risk scores have not proven to reliably predict falls in clinical settings. Machine Learning offers the potential to increase the accuracy of such predictions, possibly vastly improving care for patients at high fall risks. We devel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab528b25cc76d6e536b442fff9e20900
https://doi.org/10.3233/SHTI220530
https://doi.org/10.3233/SHTI220530
Publikováno v:
HICSS
Participatory urban planning enables citizens to make their voices heard in the urban planning process. The resulting measures are more likely to be accepted by the community. However, the participation process becomes more effortful and timeconsumin