University of Lübeck
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Swarm Learning for decentralized and confidential clinical machine learning
Stefanie Warnat‐Herresthal, Hartmut Schultze, Krishnaprasad Lingadahalli Shastry et al.
2021 · 822 Zit.
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier‐Hein, Matthias Eisenmann, Annika Reinke et al.
2018 · 359 Zit.
Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance
Thomas Dratsch, Xue Chen, Mohammad Hosein Rezazade Mehrizi et al.
2023 · 257 Zit.
Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts
Sarah Haggenmüller, Roman C. Maron, Achim Hekler et al.
2021 · 242 Zit.
Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective
Tanja Jutzi, Eva Krieghoff‐Henning, Tim Holland‐Letz et al.
2020 · 188 Zit.
Chatbots for future docs: exploring medical students’ attitudes and knowledge towards artificial intelligence and medical chatbots
Julia-Astrid Moldt, Teresa Festl‐Wietek, Amir Madany Mamlouk et al.
2023 · 174 Zit.
Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases
Francisco M. De La Vega, Shimul Chowdhury, Barry Moore et al.
2021 · 148 Zit.
Artificial Intelligence Supporting the Training of Communication Skills in the Education of Health Care Professions: Scoping Review
Tjorven Stamer, Jost Steinhäuser, Kristina Flägel
2023 · 115 Zit.
Patients’ and professionals’ views related to ethical issues in precision medicine: a mixed research synthesis
Anke Erdmann, Christoph Rehmann‐Sutter, Claudia Bozzaro
2021 · 82 Zit.
An overview and a roadmap for artificial intelligence in hematology and oncology
Wiebke Rösler, Michael Altenbuchinger, Bettina Baeßler et al.
2023 · 82 Zit.
Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations
Sarah Friedrich, Stefan Groß, Inke R. König et al.
2021 · 68 Zit.
Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours
Titus J. Brinker, Lennard Kiehl, Max Schmitt et al.
2021 · 65 Zit.
Robustness of convolutional neural networks in recognition of pigmented skin lesions
Roman C. Maron, Sarah Haggenmüller, Christof von Kalle et al.
2021 · 58 Zit.
Ensemble Deep Learning and Internet of Things‐Based Automated COVID‐19 Diagnosis Framework
Anita S. Kini, A. Nanda Gopal Reddy, Manjit Kaur et al.
2022 · 48 Zit.
Federated Learning for Decentralized Artificial Intelligence in Melanoma Diagnostics
Sarah Haggenmüller, Max Schmitt, Eva Krieghoff‐Henning et al.
2024 · 48 Zit.