Technische Universität Berlin
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Bias in data‐driven artificial intelligence systems—An introductory survey
Eirini Ntoutsi, Pavlos Fafalios, Ujwal Gadiraju et al.
2020 · 944 Zit.
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
Luca Longo, Mario Brčić, Federico Cabitza et al.
2024 · 391 Zit.
Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative
Charlene Ronquillo, Laura‐Maria Peltonen, Lisiane Pruinelli et al.
2021 · 334 Zit.
Welcome to the Era of ChatGPT et al.
Timm Teubner, Christoph M. Flath, Christof Weinhardt et al.
2023 · 320 Zit.
Where to prospectively register a systematic review
Dawid Pieper, Tanja Rombey
2022 · 176 Zit.
Explanations can be manipulated and geometry is to blame
Ann-Kathrin Dombrowski, Maximilian Alber, Christopher J. Anders et al.
2019 · 145 Zit.
The explainability paradox: Challenges for xAI in digital pathology
Theodore Evans, Carl Orge Retzlaff, Christian Geißler et al.
2022 · 127 Zit.
Toward Explainable Artificial Intelligence for Precision Pathology
Frederick Klauschen, Jonas Dippel, Philipp Keyl et al.
2023 · 104 Zit.
Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research
Toufique Ahmed Soomro, Lihong Zheng, Ahmed J. Afifi et al.
2021 · 95 Zit.
Artificial intelligence for oral and dental healthcare: Core education curriculum
Falk Schwendicke, Akhilanand Chaurasia, Thomas Wiegand et al.
2022 · 91 Zit.
Explainability and causability in digital pathology
Markus Plass, Michaela Kargl, Tim‐Rasmus Kiehl et al.
2023 · 79 Zit.
WHO and ITU establish benchmarking process for artificial intelligence in health
Thomas Wiegand, Ramesh Krishnamurthy, Monique M. Kuglitsch et al.
2019 · 68 Zit.
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology
André Homeyer, Christian Geißler, Lars Ole Schwen et al.
2022 · 61 Zit.
Fair and equitable AI in biomedical research and healthcare: Social science perspectives
Renate Baumgartner, Payal Arora, Corinna Bath et al.
2023 · 56 Zit.
Machine Learning for Health: Algorithm Auditing & Quality Control
Luis Oala, Andrew G. Murchison, Pradeep Balachandran et al.
2021 · 45 Zit.