Artificial intelligence (AI) systems for interpreting complex medical datasets

Clin Pharmacol Ther. 2017 May;101(5):585-586. doi: 10.1002/cpt.650. Epub 2017 Mar 17.


Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Artificial Intelligence / economics
  • Artificial Intelligence / trends*
  • Data Interpretation, Statistical*
  • Databases, Factual
  • Humans