Jean‐Christophe Bernhard

Application of Machine Learning Models to Predict Recurrence After Surgical Resection of Nonmetastatic Renal Cell Carcinoma

2022 · 48 Zit. · European Urology Oncology

An accurate tool to inform patients before RAPN: 3D-printed kidney model

2020 · 0 Zit. · European Urology Open Science

MP64-07 DEVELOPMENT OF AN INDIVIDUAL POSTOPERATIVE PREDICTION MODEL FOR KIDNEY CANCER RECURRENCE USING MACHINE LEARNING (UroCCR STUDY 120)

2023 · 0 Zit. · The Journal of Urology

La modélisation 3D, un support efficace de l’information-patient avant chirurgie rénale. (Étude UroCCR-39 : Rein-3D-Print)

2019 · 0 Zit. · Progrès en Urologie

Reply to: machine learning in renal cell carcinoma research: promise and pitfalls of ‘renal‐izing’ the potential of artificial intelligence

2023 · 0 Zit. · British Journal of Urology

Artificial intelligence to predict recurrence after surgical resection of non-metastatic renal cell carcinoma: Is it any better than conventional systems?

2023 · 0 Zit. · European Urology

Improvement of kidney cancer radiological education for medical students with 3D printed patient-specific models

2020 · 0 Zit. · European Urology Open Science