Laboratoire Traitement du Signal et de l'Image
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Why rankings of biomedical image analysis competitions should be interpreted with care
Lena Maier‐Hein, Matthias Eisenmann, Annika Reinke et al.
2018 · 343 Zit.
Metrics reloaded: recommendations for image analysis validation
Lena Maier‐Hein, Annika Reinke, Patrick Godau et al.
2024 · 338 Zit.
Surgical data science – from concepts toward clinical translation
Lena Maier‐Hein, Matthias Eisenmann, Duygu Sarıkaya et al.
2022 · 311 Zit.
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner et al.
2024 · 154 Zit.
BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier‐Hein, Annika Reinke, Michal Kozubek et al.
2020 · 120 Zit.
A Delphi consensus statement for digital surgery
Kyle Lam, Michael D. Abràmoff, José M. Balibrea et al.
2022 · 76 Zit.
Ethical implications of AI in robotic surgical training: A Delphi consensus statement
Justin Collins, Hani J. Marcus, Ahmed Ghazi et al.
2021 · 68 Zit.
Application of Machine Learning Models to Predict Recurrence After Surgical Resection of Nonmetastatic Renal Cell Carcinoma
Z. Khene, Pierre Bigot, N. Doumerc et al.
2022 · 48 Zit.
Surgical data science – from concepts toward clinical translation
Lena Maier‐Hein, Matthias Eisenmann, Duygu Sarikaya et al.
2021 · 39 Zit.
SAGES consensus recommendations on surgical video data use, structure, and exploration (for research in artificial intelligence, clinical quality improvement, and surgical education)
Jennifer A. Eckhoff, Guy Rosman, Maria S. Altieri et al.
2023 · 31 Zit.
Automatic matching of surgeries to predict surgeons’ next actions
Germain Forestier, François Petitjean, Laurent Riffaud et al.
2017 · 30 Zit.
Artificial Intelligence-Based Opportunities in Liver Pathology—A Systematic Review
Pierre Allaume, Noémie Rabilloud, Bruno Turlin et al.
2023 · 22 Zit.
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner et al.
2023 · 20 Zit.
Validation in the age of machine learning: A framework for describing validation with examples in transcranial magnetic stimulation and deep brain stimulation
John S. H. Baxter, Pierre Jannin
2023 · 6 Zit.
Exploring the values underlying machine learning research in medical image analysis
John S. H. Baxter, Roy Eagleson
2025 · 5 Zit.