Inserm

Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology

Elaine Johanna Limkin, Roger Sun, Laurent Dercle et al.

2017 · 763 Zit.

Electronic health records to facilitate clinical research

Martín Cowie, Juuso Blomster, Lesley H. Curtis et al.

2016 · 660 Zit.

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor et al.

2020 · 527 Zit.

Machine learning for clinical decision support in infectious diseases: a narrative review of current applications

Nathan Peiffer‐Smadja, Timothy M. Rawson, Raheelah Ahmad et al.

2019 · 522 Zit.

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Baptiste Vasey, Myura Nagendran, Bruce Campbell et al.

2022 · 443 Zit.

CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII

Burak Koçak, Bettina Baeßler, Spyridon Bakas et al.

2023 · 389 Zit.

Blockchain technology for improving clinical research quality

Mehdi Benchoufi, Philippe Ravaud

2017 · 376 Zit.

Metrics reloaded: recommendations for image analysis validation

Lena Maier‐Hein, Annika Reinke, Patrick Godau et al.

2024 · 352 Zit.

Why rankings of biomedical image analysis competitions should be interpreted with care

Lena Maier‐Hein, Matthias Eisenmann, Annika Reinke et al.

2018 · 351 Zit.

Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France

M. Lai, M Brian, Marie‐France Mamzer

2020 · 290 Zit.

Patients’ views of wearable devices and AI in healthcare: findings from the ComPaRe e-cohort

Viet-Thi Tran, Carolina Riveros, Philippe Ravaud

2019 · 283 Zit.

Open science saves lives: lessons from the COVID-19 pandemic

Lonni Besançon, Nathan Peiffer‐Smadja, Corentin Ségalas et al.

2021 · 259 Zit.

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Karim Lekadir, Alejandro F. Frangi, Antonio R. Porras et al.

2025 · 243 Zit.

Hallucination Rates and Reference Accuracy of ChatGPT and Bard for Systematic Reviews: Comparative Analysis

Mikaël Chelli, Jules Descamps, Vincent Lavoué et al.

2024 · 237 Zit.

A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI

Viknesh Sounderajah, Hutan Ashrafian, Sherri Rose et al.

2021 · 222 Zit.