Value of artificial intelligence in neuro-oncology
Cet article identifie les principales opportunités et les principaux défis à relever concernant l'utilisation de l'intelligence artificielle dans le parcours de soins neuro-oncologiques, met en évidence les nouvelles tendances en matière de modèles de base, de modélisation biophysique, de données synthétiques et de développement de médicaments puis examine les obstacles réglementaires, opérationnels et éthiques concernant l'intégration de l'intelligence artificielle en neuro-oncologie
CNS cancers are complex, difficult-to-treat malignancies that remain insufficiently understood and mostly incurable, despite decades of research efforts. Artificial intelligence (AI) is poised to reshape neuro-oncological practice and research, driving advances in medical image analysis, neuro–molecular–genetic characterisation, biomarker discovery, therapeutic target identification, tailored management strategies, and neurorehabilitation. This Review examines key opportunities and challenges associated with AI applications along the neuro-oncological care trajectory. We highlight emerging trends in foundation models, biophysical modelling, synthetic data, and drug development and discuss regulatory, operational, and ethical hurdles across data, translation, and implementation gaps. Near-term clinical translation depends on scaling validated AI solutions for well defined clinical tasks. In contrast, more experimental AI solutions offer broader potential but require technical refinement and resolution of data and regulatory challenges. Addressing both general and neuro-oncology-specific issues is essential to unlock the full potential of AI and ensure its responsible, effective, and needs-based integration into neuro-oncological practice.
The Lancet Digital Health , article en libre accès, 2025