File size: 5,892 Bytes
28f1212 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 |
# CDS Agent β Demo Video Script
> **Target length:** 3 minutes (max)
> **Format:** Screen recording with voiceover
> **Tool suggestion:** OBS Studio, Loom, or similar
---
## PRE-RECORDING CHECKLIST
- [ ] Resume HF Endpoint `medgemma-27b-cds` (~5β15 min cold start, ~$2.50/hr)
- [ ] Start backend: `cd src/backend && uvicorn app.main:app --host 0.0.0.0 --port 8000`
- [ ] Start frontend: `cd src/frontend && npm run dev`
- [ ] Open browser to `http://localhost:3000`
- [ ] Close unnecessary tabs/notifications
- [ ] Test one case end-to-end before recording to confirm endpoint is warm
- [ ] Browser zoom ~110-125% for readability on video
---
## SCRIPT
### OPENING β The Problem (0:00 β 0:30)
**[SCREEN: Title slide or the app landing page]**
> "Clinical decision-making is one of the most cognitively demanding tasks in medicine. For every patient, a clinician must simultaneously parse the history, generate a differential, recall drug interactions, remember guidelines, and synthesize a care plan β all under time pressure.
>
> Diagnostic errors affect 12 million Americans annually. Many aren't from lack of knowledge β they're from the difficulty of integrating information from multiple sources at once.
>
> CDS Agent solves this with an agentic pipeline powered by MedGemma."
---
### LIVE DEMO β The Pipeline in Action (0:30 β 2:00)
**[SCREEN: App interface β PatientInput component visible]**
> "Let me show you how it works. Here's a patient case β a 62-year-old male presenting with crushing substernal chest pain, diaphoresis, and nausea. He has a history of hypertension and diabetes, currently on lisinopril, metformin, and atorvastatin."
**[ACTION: Click a sample case button OR paste the case text, then click Submit]**
> "When I submit this case, the agent pipeline kicks off. You can see each step executing in real time on the left."
**[SCREEN: AgentPipeline component showing steps lighting up one by one]**
> "Step 1 β MedGemma parses the free-text narrative into structured patient data: demographics, vitals, labs, medications, allergies, history."
**[Wait for Step 1 to complete, ~8 seconds]**
> "Step 2 β Clinical reasoning. MedGemma generates a ranked differential diagnosis with chain-of-thought reasoning. It's considering ACS, GERD, PE, aortic dissection β weighing evidence for and against each."
**[Wait for Step 2 to complete, ~20 seconds]**
> "Step 3 β Drug interaction check. This isn't the LLM guessing β it's querying the actual OpenFDA and RxNorm databases for his three medications. Real API data, not hallucination."
**[Wait for Step 3 to complete, ~11 seconds]**
> "Step 4 β Guideline retrieval. Our RAG system searches 62 curated clinical guidelines across 14 specialties. For this case it pulls the ACC/AHA chest pain and ACS guidelines."
**[Wait for Step 4 to complete, ~10 seconds]**
> "Step 5 β and this is what makes it a real safety tool β Conflict Detection. MedGemma compares what the guidelines recommend against what the patient is actually receiving. It surfaces omissions, contradictions, dosage concerns, and monitoring gaps."
**[Wait for Step 5 to complete]**
> "Step 6 β Synthesis. Everything gets integrated into a single comprehensive report."
**[Wait for Step 6 to complete. Total pipeline ~60-90 seconds]**
---
### THE REPORT β Reviewing Results (2:00 β 2:40)
**[SCREEN: Scroll through the CDSReport component]**
> "Here's the CDS report. At the top β the ranked differential diagnosis. ACS is correctly identified as the leading diagnosis, with clear reasoning."
**[ACTION: Scroll to drug interactions section]**
> "Drug interaction warnings pulled from federal databases β not LLM-generated, real data."
**[ACTION: Scroll to Conflicts & Gaps section β highlight the red-bordered cards]**
> "This is the most important section β Conflicts and Gaps. Each card shows a specific conflict: what the guideline recommends, what the patient data shows, the severity, and a suggested resolution. These are the gaps that lead to missed diagnoses and omitted treatments in real clinical practice."
**[ACTION: Scroll to guidelines section]**
> "And finally, cited guideline recommendations from authoritative sources β ACC/AHA, ADA, and others."
---
### CLOSING β Technical & Impact (2:40 β 3:00)
**[SCREEN: Back to app overview or a summary slide]**
> "Under the hood: MedGemma 27B powers four of six pipeline steps β parsing, reasoning, conflict detection, and synthesis. It's augmented with OpenFDA and RxNorm APIs for drug safety, and a 62-guideline RAG corpus for evidence-based recommendations.
>
> We validated on 50 MedQA USMLE cases with 94% pipeline reliability and 39% diagnostic mention rate on diagnostic questions β and that's before any fine-tuning.
>
> With 140 million ED visits per year in the U.S. alone, even a modest improvement in diagnostic completeness and medication safety represents lives saved. CDS Agent is built to make that happen."
**[END]**
---
## TIMING SUMMARY
| Section | Duration | Cumulative |
|---------|----------|------------|
| Opening β The Problem | 30 sec | 0:30 |
| Live Demo β Pipeline Execution | 90 sec | 2:00 |
| Report Review | 40 sec | 2:40 |
| Closing β Tech & Impact | 20 sec | 3:00 |
## TIPS
- **Speak during pipeline wait times** β the 60-90 sec pipeline execution is perfect narration time
- **Don't rush** β the real-time pipeline visualization IS the demo; let it breathe
- **Zoom into the Conflicts section** β it's the most visually impressive and differentiating feature
- **If the endpoint is slow** β you can speed up the wait portions in post-editing (1.5Γβ2Γ speed) while keeping narration at normal speed
- **Backup plan** β if the HF endpoint is down, you can use Google AI Studio with Gemma 3 27B IT as a fallback (update .env accordingly)
|