AI Diagnostics Lab & Referral Platform
Budget: $50,000 – $100,000 USD
I’m assembling an end-to-end, cloud-based laboratory and referral platform that marries AI with routine and forensic diagnostics. The solution must cover Chemistry, Hematology and Pathology workloads and serve clinics, hospitals and government agencies—including police and army medical units—without compromise on speed, accuracy or depth of analysis.
Current blueprint
• Sample intake with AI-driven quality checks
• Instrument capture and digital pathology scanning (3DHistech / Hamamatsu)
• PyTorch models orchestrated through MLflow for pre-screening and report generation
• Clinician portal pushes real-time alerts and referral prompts
• Specialist routing and secure chain-of-custody for forensic specimens
• Cloud LIMS (OpenELIS or LabWare Cloud) as the data backbone
• FHIR/REST APIs, Keycloak SSO, TLS 1.3 and AES-256 encryption securing every transaction
Concrete deliverables
1. Production-ready architecture (IaC—Terraform or similar), complete with CI/CD pipelines
2. AI modules that consume analyzer data and whole-slide images, then return structured HL7/FHIR findings
3. Role-based web portals for lab staff, clinicians, specialists, plus a dashboard tailored to police/army stakeholders
4. Referral engine that matches cases to available specialists and dispatches notifications
5. Full documentation, automated tests and performance reports meeting ISO 15189 and GDPR/HIPAA expectations
Acceptance: a live staging environment running on synthetic data that demonstrates the entire workflow, alongside reproducible MLflow notebooks for model training and versioning.
If your expertise spans medical AI, LIMS integration and secure cloud architecture, outline your approach and timeline for these milestones so we can move straight into implementation.
Current blueprint
• Sample intake with AI-driven quality checks
• Instrument capture and digital pathology scanning (3DHistech / Hamamatsu)
• PyTorch models orchestrated through MLflow for pre-screening and report generation
• Clinician portal pushes real-time alerts and referral prompts
• Specialist routing and secure chain-of-custody for forensic specimens
• Cloud LIMS (OpenELIS or LabWare Cloud) as the data backbone
• FHIR/REST APIs, Keycloak SSO, TLS 1.3 and AES-256 encryption securing every transaction
Concrete deliverables
1. Production-ready architecture (IaC—Terraform or similar), complete with CI/CD pipelines
2. AI modules that consume analyzer data and whole-slide images, then return structured HL7/FHIR findings
3. Role-based web portals for lab staff, clinicians, specialists, plus a dashboard tailored to police/army stakeholders
4. Referral engine that matches cases to available specialists and dispatches notifications
5. Full documentation, automated tests and performance reports meeting ISO 15189 and GDPR/HIPAA expectations
Acceptance: a live staging environment running on synthetic data that demonstrates the entire workflow, alongside reproducible MLflow notebooks for model training and versioning.
If your expertise spans medical AI, LIMS integration and secure cloud architecture, outline your approach and timeline for these milestones so we can move straight into implementation.