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Community Manager Community Manager

Machine Learning and Biomarker Sub-Group Analysis for Precision Medicine

 

See how to:

  • Understand basics of machine learning
    • Compare differences between statistical modeling using data sample from a larger population and algorithmic modeling (machine learning) where data mechanism is unknown
  • Understand 4 types of models
    • Models that use different algorithms (regression, tree-based models, neural networks)
    • Models that use different parameter settings (grid search, random search, genetic algorithms)
    • Models that use different features (feature selection, feature extraction, feature engineering)
    • Models that deploy training sets (bagging, boosting, 5-fold cross validation)
  • Understand use of subgroup analysis and using subgroup identification (find correct patients for a given drug) and optimal treatment regimens (best drug for a given patient)
  • Use JMP Genomics
    • To predict death from sepsis on data collected at hospital admittance
    • To Identify differential molecular expression signatures for normal vs. polyp tissues attributable to chemoprevention therapy treatment in FAP
    • To use subgroup analyses to find clinical measures or metabolite biomarkers that exhibit 
  • Resources

 

 

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Use Videos and Resources to Practice JMP, JMP Pro, JMP Clinical and JMP Genomics.

1-hour live Mastering JMP webinars occur most Fridays from January through October. After each session, we hope you will use the video and resources shared by the presenting JMP Systems Engineers to practice what you saw.

Mastering JMP Videos are available here.