Transforming breast cancer management with real-world data and artificial intelligence

Despite the benefits, challenges remain in integrating RWD and AI into clinical practice, particularly regarding transparency, interpretability, and ethical considerations. Addressing these challenges requires robust data governance frameworks, interdisciplinary collaboration, and investment in advanced analytical tools. The potential for RWD and AI to transform breast cancer treatment and improve patient care is significant, underscoring the need for ongoing research and collaboration.

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Publication Details

Journal
ESMO Real World Data and Digital Oncology
Published
2024-08-23
DOI
https://doi.org/10.1016/j.esmorw.2024.100067
Citations
4
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
1.39
Controls
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article

Transforming breast cancer management with real-world data and artificial intelligence

Olivier Trédan, Benoîte Méry, Hugo Crochet, T. Bachelot et al.
4 citations
ESMO Real World Data and Digital Oncology
AI in cancer detection
1.39
article

Transforming breast cancer management with real-world data and artificial intelligence

Olivier Trédan, Benoîte Méry, Hugo Crochet, T. Bachelot, Pierre-Étienne Heudel
article en
4 citations

Abstract

Despite the benefits, challenges remain in integrating RWD and AI into clinical practice, particularly regarding transparency, interpretability, and ethical considerations. Addressing these challenges requires robust data governance frameworks, interdisciplinary collaboration, and investment in advanced analytical tools. The potential for RWD and AI to transform breast cancer treatment and improve patient care is significant, underscoring the need for ongoing research and collaboration.

ESMO Real World Data and Digital OncologyVol. 5
Centre Léon Bérard (FR)
Openalex Percentile: Top 16%
AI in cancer detection
1.39
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