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Medical Decision Support

Graduate · Historical course

Fall 2005

Topics

  • Introduction to Course
  • Decision Analysis 1
  • Decision Analysis 2, Linear Regression
  • Predictive Modeling, Data Collection
  • Logistic Regression, MLE
  • Evaluation
  • Instance-based Models 1 - kNN
  • Instance-based Models 2 - Trees and Rules
  • Homework 2 - Trees and Rules
  • Ensemble Models
  • PCA, LDA
  • Unsupervised Learning
  • Neural Networks
  • Survival Analysis
  • Statistical Learning Theory
  • Model Construction Schemas 1
  • Model Construction Schemas 2
  • Preprocessing Algorithms 1
  • Preprocessing Algorithms 2
  • Analysis of Problems, Complexity
  • Search Algorithms
  • Bioinformatics 1 (Hypothesis Generation, Sequence Alignment)
  • Bioinformatics 2 (Phylogenetic Trees, Haplotype Tagging)
  • Student Project Presentation 1
  • Student Project Presentation 2
Spring 2003

Topics

  • Introduction to Medical Decision Support
  • Simple Probabilistic Reasoning
  • Fuzzy & Rough Sets - Part 1
  • Fuzzy & Rough Sets - Part 2
  • Bayesian Networks - Part 1: Representation & Reasoning
  • Bayesian Networks - Part 2: Learning From Data
  • Logistic Regression - Part 1
  • Logistic Regression - Part 2
  • Unsupervised Learning
  • Classification Trees & CART
  • Artificial Neural Networks
  • Support Vector Machines
  • Evaluation of Predictive Models - Part 1
  • Evaluation of Predictive Models - Part 2
  • Optimization and Complexity
  • Survival Analysis
  • Review of Predictive Methods
  • Review of Complexity
  • Applied Informatics in Cardiology
  • Review of Clustering
  • Student Presentations

Readings

  • There is no required textbook for this course, however, the following textbooks are recommended for reference:
    Listed reading
  • Hastie, T., R. Tibshirani, and J. H. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction . (Springer Series in Statistics.) New York, NY: Springer Verlag, July 30, 2003. ISBN: 9780387952840 .
    Listed reading
  • Duda, Richard O., Peter E. Hart, and David G. Stork. Pattern Classification . 2nd ed. New York, NY: John Wiley & Sons, October 2000. ISBN: 9780471056690 .
    Listed reading
Sources