Deep learning in Electronic Health Records - CDSS 2
half-circle
vector

Deep learning in Electronic Health Records - CDSS 2

Highlights

Overview of the main principles of Deep Learning along with common architectures. Formulate the problem for time-series classification and apply it to vital signals such as ECG. Applying this methods in Electronic Health Records is challenging due to the missing values and the heterogeneity in EHR, which include both continuous, ordinal and categorical variables. Subsequently, explore imputation techniques and different encoding strategies to address these issues. Apply these approaches to formulate clinical prediction benchmarks derived from information available in MIMIC-III database.

About the Course Provider

Coursera provides access to more than 3000+ courses across a wide variety of subjects in parntership with different universities and organizations.

Course by

  • self
    Self paced
  • dueration
    Duration 32 hours
  • domain
    Domain Data Science & AI
  • subs
    Monthly Subscription
    Course is included in
    1. Starter @ AED 99 + VAT
    2. Professional @ AED 149 + VAT
  • fee
    Buy Now Option not available
  • language
    Language English