SEER Data Analysis
About Course
At AxeUSCE, we aim to empower healthcare professionals and researchers with data-driven research skills that advance medical science.
The SEER Data Analysis course provides a complete, practical introduction to analyzing cancer registry data using the Surveillance, Epidemiology, and End Results (SEER) database.
Through interactive sessions, learners will explore data extraction with SEER*Stat, apply machine learning techniques for predictive modeling, classify metastasis using real-world datasets, and perform time-to-event (survival) analysis.
A guided Google Colab notebook (SEER Machine Learning colab.ipynb) is included for hands-on practice — making it easy to run analyses without local setup.
By the end, you’ll be able to independently analyze SEER data, perform predictive modeling, and generate publication-ready research outputs.
Course Content
SEER Data Analysis: From Fundamentals to Machine Learning
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Lecture 1: SEER Database & SEER*Stat
25:00 -
Lecture 2: Machine Learning
45:59 -
Lecture 3: Metastasis Classification
24:45 -
Lecture 4: Time-to-Event (Survival Analysis)
21:22
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Student Ratings & Reviews
Your Instructor
Yasar Sattar MD M.Sc FACC
AxeUSCE is a medical education company for USMLE career guidance and research education. We train physicians and researchers for statistical analysis and research methodology. We also offer the American Board Review Crash Course.
