Predictive Analytics: Case Studies on Predictive Analytics for Healthcare

Predictive Analytics 2022    |    Beginner
  • 11 Videos | 1h 27m 23s
  • Includes Assessment
  • Earns a Badge
Healthcare aims to improve the health of individuals, but generally, healthcare systems tend to be extremely strained. Using artificial intelligence (AI) with healthcare could potentially mitigate this strain on the system. In this course, examine how AI is used in healthcare, how to evaluate classification models, and the metrics that are significant in models used in disease diagnosis. Next, discover the importance of a model's recall or sensitivity and the computation of the ROC curve and AUC metrics. Finally, explore the process of compiling the datasets, training, and evaluating models from research papers that take a general look at the application of AI in disease and specific ailment diagnosis. Upon completion, you'll be able to identify healthcare use cases for AI and its limitations.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    recall how AI can help improve outcomes in the healthcare sector
    recognize the significance of classification metrics such as accuracy, precision, and recall
    illustrate how the ROC curve and AUC metrics are computed
    outline the setup of a meta-analysis study on AI for healthcare
    identify what ML models diagnosing disease could potentially accept as input
  • list the different types of ML models used for diagnosing diseases
    outline the setup of a study on detecting heart disease using AI
    recall the performance of various models used to diagnose heart disease
    outline the setup of a study that researched the application of ML to diagnose chronic kidney disease
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 58s
    UP NEXT
  • Playable
    2. 
    The Role of AI in Healthcare
    11m 42s
  • Locked
    3. 
    Classification Model Evaluation Metrics
    7m 58s
  • Locked
    4. 
    ROC and AUC Metrics
    6m 58s
  • Locked
    5. 
    AI in Disease Diagnosis Case Study
    9m 34s
  • Locked
    6. 
    AI in Disease Diagnosis Case Study Findings
    5m 46s
  • Locked
    7. 
    AI in Disease Diagnosis Case Study Results
    9m 19s
  • Locked
    8. 
    Heart Disease Detection Case Study
    9m 20s
  • Locked
    9. 
    Heart Disease Detection Case Study Results
    10m
  • Locked
    10. 
    Chronic Kidney Disease Detection Case Study
    10m 11s
  • Locked
    11. 
    Course Summary
    4m 38s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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