Advancing brain tumor research with privacy-first AI

Sicherheitsmeldung mit Schweregrad noch nicht bewertet. Technische Details im Tab „Originaltext“; empfohlene Schritte in der Checkliste.

Originaltext der Quelle (nicht übersetzt) – die deutsche Zusammenfassung findest du im Tab „Kurzfassung".

The intersection of medicine and AI has led to remarkable innovations. However, developers now face the thorny challenge of building robust medical AI tools that have been tested and evaluated on diverse, real-world patient data while also protecting patient privacy. At Google Cloud, our approach combines strategic collaboration with Confidential Computing. To help protect both patient privacy and AI models during validation, we’re collaborating with MLCommons through the MedPerf initiative. First announced at Google Cloud Next earlier this year, this partnership uses Confidential Computing to establish a secure clean room for benchmarking AI models in real-world settings. The challenge: Evaluating AI without seeing the data MLCommons, a global community with over 125 members across tech and academia, launched MedPerf in 2023 to standardize the evaluation of medical AI. MedPerf, an open-source platform for benchmarking AI models, has advanced clinical research using federated evaluation to test models. By using Google Cloud Confidential Space, proprietary AI models can be evaluated inside hardware-isolated Trusted Execution Environments (TEEs). This special virtual machine encrypts memory in-use and hardens the operating system, so none of the parties — the hospital or research institution, other participants, or Google — can see model code or patient data while it's evaluated. Medical AI benchmarking is compute-heavy, so the Confidential VM extends beyond the CPU to the GPU. To protect model weights and patient data even during GPU-accelerated inference, MedPerf runs on …

Vollständiger Originalartikel ↗

• Betroffenheit im eigenen Stack prüfen: Versionen/Komponenten abgleichen.
• Originalquelle / Hersteller-Advisory lesen: https://cloud.google.com/blog/products/identity-security/privacy-first-medical-ai-with-medperf-and-google-cloud/
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.