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McMedHacks: Week 1/Introduction to classical machine learning

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Activités de formation

McMedHacks is an 8-week-long program that aims to teach students and researchers fundamentals of medical image analysis and deep learning in Python.

It consists of a series of in-depth workshop demos with Google Colab and seminar series given by leaders in the field. McMedHacks is a program organized by the EngerLab at McGill Medical Physics Unit and the Lady Davis Institute.

EngerLab is a part of McGill Centre for Translational Research in Cancer as well as the Cancer Research Network. 

Theme and program of week 1 : Introduction to classical machine learning

  • June 12th (Sun): Introduction to classical machine learning
  • June 15th (Wed): Classical machine learning: A case study XGBoost
  • June 17th (Fri): Introduction to image processing: Image IO and image transformations

Activities

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Featured project

Development of an automatic prognostic tool combining images and clinical data for highgrade prostate cancer.

Student member : Maxence Larose

Prostate cancer is the second most frequent cancer and the fifth leading cause of cancer death among men. To improve patient outcomes, treatment must be personalized based on accurate prognosis. Nomograms already exist to identify patients at low risk for recurrence based on preoperative clinical information, but these tools do not use patients’ medical images.

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