FRANCE Law and Practice Contributed by: Liliana Eskenazi, Julie Ernewein and Pauline Lecrenais, Fréget Glaser et Associés
Fréget Glaser et Associés 7 rue Royale 75008 Paris France Tel: +33 (0) 1 47 23 78 80 Email: contact@freget-glaser.fr Web: www.freget-glaser.fr
1. Use of Healthcare AI 1.1 Types and Applications of Healthcare AI AI is being applied across a broad range of healthcare use cases in France, with varying levels of maturity. The AI Use Observatory of the French National Agen - cy for the Performance of Health and Medico-Social Institutions (ANAP) currently includes around 50 AI- driven solutions implemented in hospitals and med - ico-social organisations. A May 2024 Senate report examined the national deployment of AI in healthcare. Key applications include the following. • Medical imaging – a leading domain for AI use, leveraging digitised scans (X-rays, CT, MRI) to enhance image quality and automate anomaly detection. These tools are widely integrated into radiologists ’workflows. The France 2030“ Santé Numérique” acceleration strategy supports this area through a EUR90 million investment. • Diagnostic tools, including: • ophthalmology – early detection of certain disease such as glaucoma and macular degeneration; • oncology – AI aids screening and diagnosis – eg, the Curie Institute developed AI to identify primary sites of metastatic cancers; the Society for Wom - en’s Imaging (SIFEM) has also highlighted promis - ing research on AI in breast cancer screening; • cardiology – improved detection of heart failure from ECGs; and • nephrology – an algorithm by Prof. Loupy predicts transplant rejection using complex patient data (Inserm Innovation Prize 2023).
• Remote patient monitoring – already used in cardiac care (eg, pacemakers, defibrillators), with predictive AI models under development to antici - pate cardiac events before symptoms appear. • Drug discovery – AI accelerates pharmaceutical R&D by analysing chemical/biological data to iden - tify candidate molecules, predict drug activity and side effects, and model interactions. • Operational and administrative optimisation – AI streamlines administrative tasks, such as schedul - ing, billing, identity checks and coding. Adoption of these technologies: • Deployment varies depending on institutional resources, funding, and trust. • According to a 2024 barometer by PulseLife and Interaction Healthcare, more than one in two healthcare professionals (53%) incorporate AI into their daily practice, particularly for assistance with access to medical information (46%), training (37%), and treatment prescription (28%). How - ever, only 58.7% of healthcare professionals trust AI for diagnostics, with algorithmic bias (59%), source transparency (50%), and the deterioration of the healthcare professional-patient relationship (49%) emerging as the main concerns. According to an OpinionWay survey for the Healthcare Data Institute, only 44% of patients believe doctors can safely use AI in care.
1.2 Key Benefits and Challenges Primary Benefits of AI in Healthcare
AI is increasingly recognised as a strategic asset in the transformation of the French healthcare system,
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