%0 Journal Article
%@ 1929-073X
%I JMIR Publications
%V 8
%N 2
%P e12100
%T Artificial Intelligence in Clinical Health Care Applications: Viewpoint
%A van Hartskamp,Michael
%A Consoli,Sergio
%A Verhaegh,Wim
%A Petkovic,Milan
%A van de Stolpe,Anja
%+ Philips Research, HTC11, p247, High Tech Campus, Eindhoven, 5656AE, Netherlands, 31 612784841, anja.van.de.stolpe@philips.com
%K artificial intelligence
%K deep learning
%K clinical data
%K Bayesian modeling
%K medical informatics
%D 2019
%7 05.04.2019
%9 Viewpoint
%J Interact J Med Res
%G English
%X The idea of artificial intelligence (AI) has a long history. It turned out, however, that reaching intelligence at human levels is more complicated than originally anticipated. Currently, we are experiencing a renewed interest in AI, fueled by an enormous increase in computing power and an even larger increase in data, in combination with improved AI technologies like deep learning. Healthcare is considered the next domain to be revolutionized by artificial intelligence. While AI approaches are excellently suited to develop certain algorithms, for biomedical applications there are specific challenges. We propose six recommendations—the 6Rs—to improve AI projects in the biomedical space, especially clinical health care, and to facilitate communication between AI scientists and medical doctors: (1) Relevant and well-defined clinical question first; (2) Right data (ie, representative and of good quality); (3) Ratio between number of patients and their variables should fit the AI method; (4) Relationship between data and ground truth should be as direct and causal as possible; (5) Regulatory ready; enabling validation; and (6) Right AI method.
%M 30950806
%R 10.2196/12100
%U https://www.i-jmr.org/2019/2/e12100/
%U https://doi.org/10.2196/12100
%U http://www.ncbi.nlm.nih.gov/pubmed/30950806