Innovation Scenarios Guide for AI Coding Skills
Scenario 1: Real-Time Radiotherapy Side-Effects Monitoring & Intelligent Alert System
Core Patient Pain Points:
- High-frequency long-term treatment (6-8 weeks, 5x/week), frequent hospital visits
- Side effects (skin inflammation, dysphagia, fatigue, myelosuppression) often unrecognized early
- Delayed feedback: subjective feeling → paper notes → review after 2 weeks
- Dose adjustments rely on doctor experience, lack real-time personalized data
Innovation Direction:
- Multi-source data: wearable devices + patient-reported outcomes + hospital systems
- AI toxicity prediction (>90% accuracy)
- 24-48 hour early detection
- Smart WeChat alerts (Low/Medium/High risk levels)
- Feedback loop for continuous model improvement
Key Skills: wearable-data-integration, patient-reported-outcomes, hospital-data-connector, sequential-thinking, n8n-wechat-automation
Expected Impact: Reduce serious complications 65-80% | Early detection 24-48h | Patient adherence↑
Scenario 2: Multi-Channel Patient Information Integration & Smart Reminder System
Core Patient Pain Points:
- Manage multiple hospital appointments, chemo schedules, medication times, follow-up dates
- Fragmented information: hospital apps, WeChat, SMS, paper cards, medical records
- Easy to miss critical events: forget meds → abnormal labs; miss appointment → treatment delay
- Family members lack unified visibility, repeatedly anxious
Innovation Direction:
- Aggregate hospital EHR + pharmacy + insurance systems
- Unified patient timeline: treatment calendar, medication schedule, test checklist
- Context-aware reminders with logistics information
- Family access with privacy control
- Medication adherence tracking with early risk detection (3-5 days advance)
Key Skills: hospital-ehr-connector, pharmacy-integration, context-aware-reminder, family-sharing-notifications, medication-adherence-tracker
Expected Impact: Medication adherence ↑85% | Early risk detection 3-5 days ahead | Family anxiety↓ | Real-world data accumulation
Scenario 3: Personalized Treatment Plan Generation & Effect Assessment System
Core Patient Pain Points:
- "Why did doctor choose this plan instead of alternatives?" - Cannot understand decision rationale
- Multi-center confusion: different hospitals, conflicting recommendations
- Long anxiety waiting for CT results (1-2 weeks)
- Treatment costs opaque, don't know future expenses
Innovation Direction:
- Multi-option comparison: 3-5 treatment schemes (chemo vs immunotherapy vs combination)
- Guideline-based + patient-factor-weighted personalized recommendations
- Real-world evidence: "Patients similar to you chose Plan A with X% response rate"
- Patient-friendly explanation with visual aids
- AI automatic CT/MRI interpretation (no need to wait for radiologist)
- Cost transparency with insurance coverage simulation
Key Skills: genomic-data-integration, sequential-thinking, image-ai-analysis, medical-content-translator, cost-tracking-and-projection, multi-center-mcp
Expected Impact: Patient understanding↑ | Doctor decision time 30% faster | Reduce multi-center confusion | Accumulate real-world evidence
Scenario 4: Multi-Channel Information Integration & Smart Reminder (Gynecological Edition)
Innovation Enhancement:
- Menstrual cycle awareness (mark dates, avoid certain treatment days)
- Hormone management (e.g., "HER2+ patient: ensure ≥3 weeks between trastuzumab injections")
- Quality of life feedback (menstrual recovery, sexual function, fertility desire)
- Spouse/family participation with patient consent
Expected Impact: Chemo adherence ↑90% | Hormone therapy adherence ↑85% | Family involvement↑
Scenario 5: Personalized Treatment Plan & Gynecology-Specific Assessment
Multi-Disciplinary Integration:
- Ovarian cancer: chemo vs chemo+targeted vs chemo+immunotherapy
- Endometrial cancer: surgery+observation vs surgery+chemo vs surgery+chemo+radiotherapy
- Cervical cancer: radiotherapy vs chemoradiotherapy vs neoadjuvant chemo+surgery
- Special considerations: fertility preservation options, hormone therapy timeline (5-10 years), cost planning
Key Skills: multi-cancer-routing, sequential-thinking, visual-outcome-display, cost-tracking-and-projection
Expected Impact: Understand multi-disciplinary decisions | Clear long-term timeline | Fertility questions answered | Cost transparency
Scenario 6: Chemotherapy Toxicity & Sexual/Fertility Function Real-Time Monitoring
Core Patient Pain Points:
- Young patients most concerned: "Will I become permanently infertile? Will menstruation return?"
- Current approach: passive monitoring, patients anxious about missing fertility preservation window
- Critical: freezing eggs has optimal timing windows during chemo
Innovation Direction:
- Data integration: wearables + menstrual calendar + hormone levels + ovarian function markers
- AI ovarian reserve predictor (based on chemo regimen, baseline AMH) → predict post-chemo function retention % and best egg-freezing window
- Monthly fertility/sexuality questionnaires
- Fertility preservation alerts: "Freeze eggs NOW - last chance window closing"
- Long-term recovery coaching: menstrual recovery guides, sexual function rehabilitation, safe pregnancy timing
Key Metrics: AMH levels | Menstrual interval | Cardiac function (LVEF) | Sexual function | Fertility assessment
Key Skills: wearable-data-integration, patient-calendar, sequential-thinking, lifestyle-questionnaire, fertility-preservation-alerts, recovery-coaching
Expected Impact: Preserve fertility options | Clear recovery trajectory | Professional guidance for psychosocial support | Relationship maintenance