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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

Detection of delirium using physiological parameters and hypovigilance monitoring: a pilot observational cohort study

Student member : Raphaëlle Giguère

Delirium is a condition that, when left unmanaged, is associated with increased mortality and longer hospitalization of patients in intensive care; therefore, its detection should be an integral part of care. It is characterized by confusion, anxiety and reduced alertness. It is estimated that 75% of delirium cases are not detected on admission to hospital. Detecting such an acute condition requires frequent monitoring of participants, which is labor intensive and requires expertise.

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