OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 28.04.2026, 08:26

Technische Universität Dresden

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Meistzitierte Publikationen im Bereich Gesundheit & MedTech

The future landscape of large language models in medicine

Jan Clusmann, Fiona R. Kolbinger, Hannah Sophie Muti et al.

2023 · 875 Zit.

CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII

Burak Koçak, Bettina Baeßler, Spyridon Bakas et al.

2023 · 389 Zit.

Metrics reloaded: recommendations for image analysis validation

Lena Maier‐Hein, Annika Reinke, Patrick Godau et al.

2024 · 352 Zit.

Large language model AI chatbots require approval as medical devices

Stephen Gilbert, Hugh Harvey, Tom Melvin et al.

2023 · 190 Zit.

A guide to artificial intelligence for cancer researchers

Raquel Pérez-López, Narmin Ghaffari Laleh, Faisal Mahmood et al.

2024 · 167 Zit.

Artificial intelligence and increasing misinformation

Scott Monteith, Tasha Glenn, John Geddes et al.

2023 · 154 Zit.

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Tirtha Chanda, Katja Hauser, Sarah Hobelsberger et al.

2024 · 129 Zit.

Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis

Fiona R. Kolbinger, Gregory Patrick Veldhuizen, Jiefu Zhu et al.

2024 · 112 Zit.

A future role for health applications of large language models depends on regulators enforcing safety standards

Oscar Freyer, Isabella C. Wiest, Jakob Nikolas Kather et al.

2024 · 111 Zit.

Adversarial attacks and adversarial robustness in computational pathology

Narmin Ghaffari Laleh, Daniel Truhn, Gregory Patrick Veldhuizen et al.

2022 · 105 Zit.

Reinforcement Learning for Precision Oncology

Jan‐Niklas Eckardt, Karsten Wendt, Martin Bornhäuser et al.

2021 · 82 Zit.

A Delphi consensus statement for digital surgery

Kyle Lam, Michael D. Abràmoff, José M. Balibrea et al.

2022 · 80 Zit.

Artificial Intelligence-Assisted Surgery: Potential and Challenges

Sebastian Bodenstedt, Martin Wagner, Beat P. Müller‐Stich et al.

2020 · 77 Zit.

New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology

Bouchra Derraz, Gabrièle Bréda, C. Kaempf et al.

2024 · 73 Zit.

Algorithm Change Protocols in the Regulation of Adaptive Machine Learning–Based Medical Devices

Stephen Gilbert, Matthew Fenech, Martin C. Hirsch et al.

2021 · 72 Zit.