PatientStories.ai: AI-native transformation of narrative medicine into structured clinical insight.
Current product and architecture work translating patient stories into structured, privacy-aware signals for research planning, patient-centered trial design, and real-world evidence translation.
AI-native narrative transformation
The core concept converts narrative medicine into AI-native data workflows: patient stories, inferred structure, gap prompts, check-ins, pattern detection, and structured signals.
Figma-driven clinical app prototyping
The work includes prompt-driven interface design, modal flows, onboarding concepts, consent UX, participant value exchange, and patient-centered trial-adjacent capture.
Security and trust layers
The design includes magic-link access, bot-friction concepts, consent-before-PHI thinking, PII/PHI separation, privacy-aware email logic, and audit/export thinking.
Patient-centered clinical trial apps
PatientStories links patient check-ins, community insights, narrative capture, targeted prompts, and research-partner workflows into a patient-centered app model.
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