PRISMA — Clinical AI for Oncology
Oncology-focused clinical reasoning prototype with local LLM via Ollama, semantic literature search (RAG), and auditable case analysis workflow.
Data inference
100% local
privacy model documented
Local latency (doc)
30-50ms
technical comparison vs external APIs
Demo cases
2 cases
liver and lung oncology
Challenge
Deliver AI support for clinical teams without exposing sensitive patient data to external APIs while preserving analysis speed.
Solution
Local-first architecture with Llama 3 via Ollama, ChromaDB for medical literature retrieval, and fallback behavior when AI services are unavailable.
Key outcomes
- Local inference keeps sensitive data inside clinical perimeter
- End-to-end flow: patient data → literature → recommendation
- Two complete oncology demo cases for validation
- Operational fallback when Ollama/ChromaDB are offline
casesPage.labels.architecture
A solução foi construída sobre uma base técnica resiliente, priorizando performance e escalabilidade. Cada camada foi otimizada para os requisitos específicos do projeto.
Stack Visualization Active
casesPage.labels.features
Local LLM for medical data privacy
Semantic search over medical literature
Clinical metrics and correlation visualizations
Traceable clinical analysis workflow
Visual fallback mode for service continuity
casesPage.labels.gallery
Module_View_01.jpg
Module_View_02.jpg
Module_View_03.jpg