University Hospital of Zurich
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Preoperative anaemia and postoperative outcomes in non-cardiac surgery: a retrospective cohort study
Khaled M. Musallam, Hani Tamim, Toby Richards et al.
2011 · 1.228 Zit.
International consensus statement on the peri‐operative management of anaemia and iron deficiency
Manuel Múñoz, Austin G. Acheson, Michael Auerbach et al.
2016 · 810 Zit.
Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis
Urs J. Muehlematter, Paola Daniore, Kerstin Noëlle Vokinger
2021 · 595 Zit.
Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions
Tugba Akinci D’Antonoli, Arnaldo Stanzione, Christian Bluethgen et al.
2023 · 185 Zit.
Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care
Fadila Zerka, Samir Barakat, Seán Walsh et al.
2020 · 131 Zit.
Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma
Tirtha Chanda, Katja Hauser, Sarah Hobelsberger et al.
2024 · 124 Zit.
Generative artificial intelligence in primary care: an online survey of UK general practitioners
Charlotte Blease, Cosima Locher, Jens Gaab et al.
2024 · 117 Zit.
Solving the explainable AI conundrum by bridging clinicians’ needs and developers’ goals
Nadine Bienefeld, J. M. Boss, Rahel Lüthy et al.
2023 · 113 Zit.
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
Burak Koçak, Andrea Ponsiglione, Arnaldo Stanzione et al.
2024 · 108 Zit.
Clinical Deployment of Explainable Artificial Intelligence of SPECT for Diagnosis of Coronary Artery Disease
Yuka Otaki, Ananya Singh, Paul Kavanagh et al.
2021 · 107 Zit.
Use of artificial intelligence in critical care: opportunities and obstacles
Michael R. Pinsky, Armando Bedoya, Azra Bihorac et al.
2024 · 101 Zit.
Detection and localization of distal radius fractures: Deep learning system versus radiologists
Christian Blüthgen, Anton S. Becker, I. Martini et al.
2020 · 95 Zit.
FDA-cleared artificial intelligence and machine learning-based medical devices and their 510(k) predicate networks
Urs J. Muehlematter, Christian Bluethgen, Kerstin Noëlle Vokinger
2023 · 85 Zit.
Machine learning in neurosurgery: a global survey
Victor E. Staartjes, Vittorio Stumpo, Julius M. Kernbach et al.
2020 · 79 Zit.
An overview and a roadmap for artificial intelligence in hematology and oncology
Wiebke Rösler, Michael Altenbuchinger, Bettina Baeßler et al.
2023 · 77 Zit.