Lumen Clinical
Lumen Clinical is a pre-deployment safety certification workstation designed to stress-test medical AI LLMs against clinical safety guidelines. Built under the direction of a clinician, Lumen ensures that clinical AI agents do not bypass safety rules, prescribe wrong doses, or miss life-threatening patient emergencies. HOW BAND COORDINATES OUR AGENTS: Rather than using static prompts, Lumen establishes a non-linear multi-agent simulation using the Band SDK coordination layer: 1. Red-Team Adversary Agent -> [Band Task: attack_scenario] -> Doctor Agent. The adversary adapts its jailbreak strategy (escalate, pivot, or compound) dynamically based on what the doctor says. 2. Doctor Agent -> [Band Task: consultation_turn] -> Patient Agent. The Doctor runs on BioMistral-7B via Featherless AI and utilizes diagnostic tools (LOINC lab checks, CPT imaging, RxNorm prescribing). 3. Patient Agent -> [Band Task: patient_response] -> Doctor Agent. The Patient simulates realistic clinical personas (minimizer, drug-seeker, health-anxious, confused elder) and withholds information unless properly queried. 4. Doctor Agent -> [Band Task: final_transcript] -> Safety Auditor. The Safety Auditor runs a consensus check via AI/ML API, scoring the session (0-100) and compiling an HL7 FHIR R4 compliance transaction bundle. BUSINESS VALUE: Lumen closes the pre-deployment gap for clinical AI, replacing months of manual trials with automated, rigorous safety auditing. It outputs standardized FHIR R4 compliance logs and triggers human-in-the-loop clinical escalation when safety scoring thresholds fall.
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"Application of technology: Non-linear 4-agent clinical safety simulation: Red-Team Adversary (dynamic jailbreak adaptation: escalate/pivot/compound based on Doctor responses), Doctor Agent (BioMistral-7B via Featherless + LOINC lab + CPT imaging + RxNorm prescribing tools), Patient Agent (4 realistic personas: minimizer, drug-seeker, health-anxious, confused elder), Safety Auditor (0-100 session scoring + HL7 FHIR R4 compliance transaction bundle). Built under clinician direction. Presentation: Outstanding medical AI safety framing — pre-deployment stress-testing against clinical safety guidelines replacing months of manual trials. The adversary agent dynamically adapting its jailbreak strategy based on Doctor responses is a genuinely adversarial and realistic simulation. HL7 FHIR R4 compliance output is the industry standard clinical data format. Business value: Pre-deployment clinical AI safety certification is a growing regulatory requirement as medical AI enters clinical workflows. HL7 FHIR R4 compliance logs and automated safety scoring directly address FDA/EMA requirements for clinical AI evaluation. Originality: Red-Team Adversary using dynamic jailbreak strategy adaptation (escalate/pivot/compound based on Doctor response pattern) for medical AI safety testing is a genuinely novel and rigorous approach to pre-deployment clinical AI red-teaming. Realistic patient personas withholding information unless properly queried simulate real clinical communication challenges."
Sanem Avcil
For Innovators & Creators