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WHO, large multimodal models and governance of AI in healthcare

Large multimodal models can combine text, image, audio and other signals, but they require governance proportional to the clinical and institutional risk.

WHO guidance on ethics and governance of AI for health, large multimodal models, risks, evidence, transparency and supervision.

01

Governança proporcional ao risco

Broad applications require risk control

The WHO's 2024 guidance on large multimodal models in healthcare emphasizes ethics, governance, validation, transparency, accountability and care with uses in patient care, research and public health.

02

Da capacidade técnica ao uso responsável

From technical promise to responsible use

The value of the model depends on evidence, safety, human supervision, fit to the local context, data protection and monitoring after deployment.

03

Use in medicine

Text, image and multimodal data

Multimodal models can support documentation, search, image analysis and knowledge synthesis. In a clinical setting, each use needs its own purpose, limit and validation.

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Strategic intelligence for healthcare. From complexity to clarity.

For workflows with sensitive data, we apply minimization and de-identification before any processing by language models, under double data anonymization. We use AI providers via the OpenAI and Google Gemini APIs under enterprise terms, with ZDR (Zero Data Retention) and BAA (Business Associate Agreement) enabled for eligible endpoints.

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