Your browser doesn't support javascript.
loading
Artificial intelligence (AI) systems for interpreting complex medical datasets.
Altman, R B.
Affiliation
  • Altman RB; Stanford University, Stanford, California, USA.
Clin Pharmacol Ther ; 101(5): 585-586, 2017 May.
Article in En | MEDLINE | ID: mdl-28182259
ABSTRACT
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Data Interpretation, Statistical Limits: Humans Language: En Journal: Clin Pharmacol Ther Year: 2017 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Data Interpretation, Statistical Limits: Humans Language: En Journal: Clin Pharmacol Ther Year: 2017 Document type: Article Affiliation country: United States