Onze Lieve Vrouwziekenhuis Hospital

Generative artificial intelligence in surgery

Severin Rodler, Conner Ganjavi, Pieter De Backer et al.

2024 · 45 Zit.

Predicting intra‐operative and postoperative consequential events using machine‐learning techniques in patients undergoing robot‐assisted partial nephrectomy: a Vattikuti Collective Quality Initiative database study

Mahendra Bhandari, Anubhav Reddy Nallabasannagari, Madhu Reddiboina et al.

2020 · 28 Zit.

GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment

Severin Rodler, Francesco Cei, Conner Ganjavi et al.

2025 · 17 Zit.

AI-Enabled ECG Analysis Improves Diagnostic Accuracy and Reduces False STEMI Activations

Robert Herman, Bryn E. Mumma, Jake D. Hoyne et al.

2025 · 11 Zit.

Intraclass correlation metrics for the accuracy of algorithmic definitions in a computerized decision support system for supportive cancer care

Matti Aapro, Ivo Abraham, Karen MacDonald et al.

2007 · 5 Zit.

Privacy-proof Live Surgery Streaming

Pieter De Backer, Jente Simoens, Kenzo Mestdagh et al.

2024 · 5 Zit.

What More Can We Ask of Robotics?

Peter Wiklund, Silvia Rebuffo, Nicola Frego et al.

2023 · 5 Zit.

Faculty Opinions recommendation of Artificial intelligence and machine learning in anesthesiology.

Jan F. A. Hendrickx

2019 · 0 Zit.

Deep learning for mortality prediction in patients with a de-novo or worsened heart failure

Robert Herman, Marc Vanderheyden, Boris Vavrik et al.

2021 · 0 Zit.

The data dividend: how AI turns robotic surgery into measurable value. Insight from EAU-YAU Urotechnology and Digital Health Working Group

Pieter De Backer, Severin RODLER, Karl F. KOWALEWSKI et al.

2026 · 0 Zit.

Abstract 13836: Unbiased Deep Learning Approach Utilizing Longitudinal Data in Assessing All-Cause Mortality in Patients With a <i>De Novo</i> or Worsened Heart Failure

Robert Herman, Marc Vanderheyden, Boris Vavrik et al.

2021 · 0 Zit.