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  • Book
    MIT Critical Data.
    Contents:
    Introduction to the Book
    Objectives of secondary analysis of EHR data
    Review of clinical database
    Challenges and opportunities
    Secondary Analysis of EHR Data Cookbook
    Overview
    Step 1: Formulate research question
    Step 2: Data extraction and preprocessing
    Step 3: Exploratory Analysis
    Step 4: Data analysis
    Step 5: Validation and sensitivity analysis
    Missing Data
    Noise vs. Outliers
    Case Studies
    Introduction
    Predictive Modeling: outcome prediction (discrete)
    Predictive Modeling: dose optimization (regression)
    Pharmacovigilance (classification)
    Comparative effectiveness: propensity score analysis
    Comparative effectiveness: instrumental variable analysis
    Decision and Cost Effectiveness Analysis: Hidden Markov models and Monte Carlo simulation
    Time series analysis: Gaussian processes (ICP modelling)
    Time series analysis: Bayesian inference (Motif discovery in numerical signals)
    Time Series analysis: Optimization techniques for hyperparameter selection
    Signal processing: analysis of waveform data
    Signal processing: False alarm reduction.
    Digital Access Springer 2016