University Hospital Frankfurt
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
International consensus statement on the peri‐operative management of anaemia and iron deficiency
Manuel Múñoz, Austin G. Acheson, Michael Auerbach et al.
2016 · 827 Zit.
Automated Gleason grading of prostate cancer tissue microarrays via deep learning
Eirini Arvaniti, Kim S. Fricker, Michaël Moret et al.
2018 · 426 Zit.
Large language models for structured reporting in radiology: past, present, and future
Felix Busch, Lena Hoffmann, Daniel Santos et al.
2024 · 88 Zit.
An overview and a roadmap for artificial intelligence in hematology and oncology
Wiebke Rösler, Michael Altenbuchinger, Bettina Baeßler et al.
2023 · 81 Zit.
Artificial Intelligence and Machine Learning in Radiology
Julian L. Wichmann, Martin J. Willemink, Carlo N. De Cecco
2020 · 78 Zit.
Developing, purchasing, implementing and monitoring AI tools in radiology: practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA
Adrian P. Brady, Bibb Allen, Jaron Chong et al.
2024 · 73 Zit.
Joint Imaging Platform for Federated Clinical Data Analytics
Jonas Scherer, Marco Nolden, Jens Kleesiek et al.
2020 · 70 Zit.
Guiding AI in radiology: ESR’s recommendations for effective implementation of the European AI Act
Elmar Kotter, Tugba Akinci D’Antonoli, Renato Cuocolo et al.
2025 · 69 Zit.
Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method
Christian Booz, İbrahim Yel, Julian L. Wichmann et al.
2020 · 68 Zit.
Automated Gleason grading of prostate cancer tissue microarrays via deep learning
Eirini Arvaniti, Kim S. Fricker, Michaël Moret et al.
2018 · 63 Zit.
Must-have Qualities of Clinical Research on Artificial Intelligence and Machine Learning
Burak Koçak, Renato Cuocolo, Daniel Santos et al.
2022 · 58 Zit.
Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA
Adrian P. Brady, Bibb Allen, Jaron Chong et al.
2024 · 52 Zit.
Artificial intelligence, machine learning and deep learning in musculoskeletal imaging: Current applications
Tommaso D’Angelo, Danilo Caudo, Alfredo Blandino et al.
2022 · 52 Zit.
Reproducibility of radiomics quality score: an intra- and inter-rater reliability study
Tugba Akinci D’Antonoli, Armando Ugo Cavallo, Federica Vernuccio et al.
2023 · 50 Zit.
Towards reproducible radiomics research: introduction of a database for radiomics studies
Tugba Akinci D’Antonoli, Renato Cuocolo, Bettina Baeßler et al.
2023 · 45 Zit.