Délégation Paris 7

Demystification of AI-driven medical image interpretation: past, present and future

Peter Savadjiev, Jaron Chong, Anthony Dohan et al.

2018 · 150 Zit.

Machine Learning for COVID-19 needs global collaboration and data-sharing

Nathan Peiffer‐Smadja, Redwan Maatoug, François-Xavier Lescure et al.

2020 · 76 Zit.

What’s new in ICU in 2050: big data and machine learning

Sébastien Bailly, Geert Meyfroidt, Jean‐François Timsit

2017 · 62 Zit.

Artificial intelligence for oral and maxillo-facial surgery: A narrative review

S. Rasteau, D. Ernenwein, Charles Savoldelli et al.

2022 · 61 Zit.

A systematic review of retracted publications in emergency medicine

Anthony Chauvin, C. de Villelongue, Dominique Pateron et al.

2017 · 46 Zit.

Deep medicine, artificial intelligence, and the practising clinician

Claude Matuchansky

2019 · 19 Zit.

Machine learning to predict antimicrobial resistance: future applications in clinical practice?

Yousra Kherabi, Michaël Thy, Donia Bouzid et al.

2024 · 18 Zit.

Data capture by digital pen in clinical trials: A qualitative and quantitative study

Candice Estellat, Florence Tubach, Yolande Costa et al.

2007 · 15 Zit.

Intelligence clinique et intelligence artificielle

Claude Matuchansky

2019 · 14 Zit.

Ethical Aspects of Artificial Intelligence in Radiation Oncology

L. Lahmi, Marie‐France Mamzer, Anita Burgun et al.

2022 · 12 Zit.

How is Video Efficient to Diagnose Sport-Related Concussion? A Cross-Sectional Study in the French TOP14 Rugby Championship

Charlotte Gil, Madalina Jacota, Yohan Caudron et al.

2021 · 3 Zit.

Exploring the Bedside Clinician’s Medical Intelligence in the Age of Artificial Intelligence

Claude Matuchansky

2019 · 2 Zit.

FO051THE IMPACT OF GFR EVALUATION TECHNIQUE ON LIVING KIDNEY DONATION ELIGIBILITY

F. Gaillard, Marie Courbebaisse, Nassim Kamar et al.

2018 · 0 Zit.