Benefits, Pitfalls, and Potential Bias in Health Care AI.

Clicks: 411
ID: 2185
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Star

Ranked #4 of 24 articles by views in north carolina medical journal

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
As the health care industry adopts artificial intelligence, machine learning, and other modeling techniques, it is seeing benefits to both patient outcomes and cost reduction; however, it needs to be cognizant of and ensure proper management of the risks, including bias. Lessons learned from other industries may provide a framework for acknowledging and managing data, machine, and human biases that arise while implementing AI.
Reference Key
haguebenefitsnorth Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hague, Douglas C;
Journal north carolina medical journal
Year Year not found
DOI
10.18043/ncm.80.4.219
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.