#healthdata

Short answer: treat consent as a typed, expiring authorization record, and make account deletion...

Short answer: model consent as a state transition with a category gate, a bounded grant, and an...

Short answer: in a health-services marketplace, password recovery may restore account access, but it...

Short answer: treat consent as a recoverable state machine, not a checkbox. Classify the data and...

Samsung Health began prompting users to consent to AI training on intimate data including sleep, nutrition, medication and cycle tracking, with reports that declining costs cloud sync - a consent-under-duress pattern privacy law treats as invalid.

Democrats want AI health data sales banned, with a 180-day enforcement clock and chatbot medical disclosures in scope.

Yes. GP practices can use AI scribes, but as independent contractors they are data controllers in their own right: the DPIA, lawful basis, patient notice and vendor contract all land on the practice,

Originally published at norvik.tech Introduction Dive deep into how calibrating your...

This week, two of Europe's most important health informatics gatherings open within seventy-two hours...

QIS outcome packets are PHI-free not by policy, not by de-identification, not by differential privacy noise — but by construction. The distillation step produces derived population statistics that never contained patient-level data. Here is the formal argument for HIPAA Safe Harbor, GDPR Article 26, and EHDS secondary use compliance.

TensorFlow Federated solves model training across distributed data. QIS solves what happens between training rounds — routing validated outcomes so the next round starts smarter. For federated learning practitioners evaluating distributed health intelligence architectures.

EHDS requires cross-border health data intelligence. NFDI4Health needs distributed routing. GDI needs genomic outcome synthesis. All three assume a central broker. QIS removes the broker and the intelligence still scales — quadratically.