Hôpital Pellegrin

Five simultaneous artificial intelligence data challenges on ultrasound, CT, and MRI

Nathalie Lassau, Théo Estienne, P. de Vomecourt et al.

2019 · 43 Zit.

Assessment of performances of a deep learning algorithm for the detection of limbs and pelvic fractures, dislocations, focal bone lesions, and elbow effusions on trauma X-rays

Nor-Eddine Regnard, Boubekeur Lanseur, Jeanne Ventre et al.

2022 · 37 Zit.

“Artificial intelligence”: Which services, which applications, which results and which development today in clinical research? Which impact on the quality of care? Which recommendations?

Vincent Diebolt, I Azancot, François‐Henri Boissel et al.

2018 · 15 Zit.

Comment on Starke et al.: ‘Computing schizophrenia: ethical challenges for machine learning in psychiatry’: from machine learning to student learning: pedagogical challenges for psychiatry

Christophe Gauld, Jean‐Arthur Micoulaud‐Franchi, Guillaume Dumas

2020 · 13 Zit.

Is the information provided by large language models valid in educating patients about adolescent idiopathic scoliosis? An evaluation of content, clarity, and empathy

Siegmund Lang, Jacopo Antonino Vitale, Fabio Galbusera et al.

2024 · 11 Zit.

Comment on Starke et al.: “Computing schizophrenia: ethical challenges for machine learning in psychiatry”: From machine learning to student learning: pedagogical challenges for psychiatry – Corrigendum

Christophe Gauld, Jean‐Arthur Micoulaud‐Franchi, Guillaume Dumas

2021 · 4 Zit.

Understanding the challenges to implementing AI solutions in radiology departments and how to overcome them: A comprehensive review endorsed by the French College of Radiologists (CERF) and the French Society of Radiology (SFR)

Amandine Crombé, Camille Bourillon, Stéphane Chaillou et al.

2025 · 2 Zit.

Imaging in France: 2024 Update

Maxime Barat, Amandine Crombé, Tom Boeken et al.

2024 · 2 Zit.

« Intelligence artificielle » : quels services, quelles applications, quels résultats et quelle valorisation aujourd’hui en recherche clinique ? Quel impact sur la qualité des soins ? Quelles recommandations ?

Vincent Diebolt, I Azancot, François‐Henri Boissel et al.

2018 · 1 Zit.

A Counterfactual LLM Framework for Detecting Human Biases: A Case Study of Sex/Gender in Emergency Triage

Ariel Guerra-Adames, Marta Avalos-Fernandez, Océane Dorémus et al.

2025 · 0 Zit.

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

A. De Hauteclocque, C. Michiels, Julien Sarrazin et al.

2019 · 0 Zit.

Real-life performance of AI-aided radiologists, emergency physicians and two AI solutions for diagnosing bone fractures in appendicular skeletal trauma

Amandine Crombé, A. Ben Cheikh, Mylène Seux et al.

2025 · 0 Zit.

Exploring AI: Transforming medical practice, education and research

Bernhard Haid, Caleb P. Nelson, Muhammet İrfan Dönmez et al.

2024 · 0 Zit.

Évaluation de l’intelligence artificielle : 30 questions ouvertes posées à ChatGPT

J. Lasnier Siron, Anthony A. Bertrand, Marie Kostine et al.

2023 · 0 Zit.