Predictive Analytics in Healthcare Literacy (Beginner Level)

  • 9m
  • 9 questions
The Predictive Analytics in Healthcare Literacy (Beginner Level) benchmark measures your ability to identify the need for artificial intelligence (AI) and predictive analytics in the healthcare domain. You will be evaluated on your skills in identifying various use cases where one can apply predictive analytics. A learner who scores high on this benchmark demonstrates that they have a good understanding of predictive analytics needs and various use cases in healthcare.

Topics covered

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