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odafeng/README.md

Shih-Feng Huang 黃士峯

Surgical Data Scientist · Colorectal Surgeon
clinical problems → structured data → deployable systems

I build end-to-end surgical data systems — turning raw CT, intraoperative video, and postoperative records into reproducible analysis and deployable clinical tools.

高雄榮總大腸直腸外科主治醫師
專注於將臨床問題轉化為可計算、可重現、可部署的資料科學系統

⚙️ Surgical Data Pipeline (Core System)

            CT Imaging
                │
         Feature Extraction
                │
        Difficulty Modeling
                │
   Intraoperative Video / Workflow Analysis
                │
   Postoperative Outcomes / PRO / Prediction

🧠 Preoperative

  • Automated CT-based pelvimetry
  • Surgical difficulty modeling (FREDRIC framework)

🎥 Intraoperative

  • Learning curve modeling (RA-CUSUM)
  • Video-based workflow analysis

📊 Postoperative

  • Outcome prediction (ML / survival analysis)
  • Digital follow-up & PRO systems

🚀 Featured Systems

🔬 CT Pelvimetry Pipeline

ctpelvimetry — 🟢 pip install ctpelvimetry → Fully automated CT-based pelvimetry → Published & validated (IJCARS) · distributed via PyPI

📈 Learning Curve Intelligence

rissa-ML-learning-curve — 📄 paper + code → ML-based surgical safety profiling → Published in Journal of Robotic Surgery

📊 Clinical Outcome Modeling

Stage_III_Colon_EDR — 📄 research code → Early recurrence prediction → Multi-center validation

📱 Surgical Follow-up Platform

hemorrhoids-postop — 🔒 IRB study · deployed → Digital postoperative monitoring system → Deployed in IRB-approved clinical study

🎥 Surgical Video Analytics

cholec80-phase-recognition — 🟢 open-source · active → Automated surgical phase recognition → Two-stage pipeline: MS-TCN (non-causal) vs TeCNO (causal MS-TCN)

📚 Selected Publications

Focus: surgical AI, learning curves, and outcome modeling

  • Machine learning–based learning curve analysis — J Robotic Surg. 2026 doi
  • Video-based RA-CUSUM proficiency assessment — Int J Colorectal Dis. 2026 doi
  • Robotic single-stapling vs double-stapling anastomosis — J Robotic Surg. 2025 doi

Full list → ORCID

🧰 Methods & Stack

  • Data Science: pandas, scikit-learn, lifelines, PyTorch
  • Imaging: CT processing, TotalSegmentator, 3D Slicer
  • Causal Inference: overlap weighting, RMST, survival modeling
  • Systems: Next.js, TypeScript, PostgreSQL

🧭 Direction

Building the infrastructure of Surgical Data Science:

  • From clinical intuition → quantitative modeling
  • From retrospective data → real-time systems
  • From isolated studies → reproducible pipelines
  • Now building: surgical video analytics — automated phase recognition & workflow decomposition (cholec80-phase-recognition: MS-TCN vs causal TeCNO)

Pinned Loading

  1. rissa-ML-learning-curve rissa-ML-learning-curve Public

    ML-based risk modeling for learning curve assessment in robotic left-sided colorectal cancer surgery

    Jupyter Notebook

  2. Stage_III_Colon_EDR Stage_III_Colon_EDR Public

    Analysis pipeline for developing and externally validating a four-variable pathology-based model to predict early distant recurrence (within 18 months) in stage III colon cancer. The repository con…

    Jupyter Notebook

  3. ctpelvimetry ctpelvimetry Public

    Automated CT pelvimetry and body composition analysis

    Python

  4. hemorrhoids-postop hemorrhoids-postop Public

    Hemorrhoid postoperative symptom monitoring and AI-assisted patient education PWA — React + Supabase + Claude API

    HTML

  5. MedFeedJournalTracker MedFeedJournalTracker Public

    MedFeed 是一套專為醫學與科研人員打造的自動化期刊追蹤系統，目標是簡化最新學術文章的蒐集、篩選與推播流程。使用者可事先定義關注的期刊、類別標籤（如 CRC：大腸直腸癌、SDS：外科數據科學），並透過 Line 推播接收每日最新成果。

    Python 1

  6. cholec80-phase-recognition cholec80-phase-recognition Public

    Cholec80 surgical phase recognition: two-stage pipeline comparing MS-TCN (non-causal) vs TeCNO (causal MS-TCN)

    Python