the 2013 symposium on pathology data integration and clinical decision support and the current state of field
Clicks: 337
ID: 175703
2014
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.
Reader Engagement
Steady Performance
30.0
/100
337 views
60 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #5 of 24 articles by views in annual review of materials science
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate 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
Background: Pathologists and informaticians are becoming increasingly interested in electronic clinical decision support for pathology, laboratory medicine and clinical diagnosis. Improved decision support may optimize laboratory test selection, improve test result interpretation and permit the extraction of enhanced diagnostic information from existing laboratory data. Nonetheless, the field of pathology decision support is still developing. To facilitate the exchange of ideas and preliminary studies, we convened a symposium entitled: Pathology data integration and clinical decision support. Methods: The symposium was held at the Massachusetts General Hospital, on May 10, 2013. Participants were selected to represent diverse backgrounds and interests and were from nine different institutions in eight different states. Results: The day included 16 plenary talks and three panel discussions, together covering four broad areas. Summaries of each presentation are included in this manuscript. Conclusions: A number of recurrent themes emerged from the symposium. Among the most pervasive was the dichotomy between diagnostic data and diagnostic information, including the opportunities that laboratories may have to use electronic systems and algorithms to convert the data they generate into more useful information. Differences between human talents and computer abilities were described; well-designed symbioses between humans and computers may ultimately optimize diagnosis. Another key theme related to the unique needs and challenges in providing decision support for genomics and other emerging diagnostic modalities. Finally, many talks relayed how the barriers to bringing decision support toward reality are primarily personnel, political, infrastructural and administrative challenges rather than technological limitations.
| Reference Key |
baron2014journalthe
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Jason M Baron;Anand S Dighe;Ramy Arnaout;Ulysses J Balis;W Stephen Black-Schaffer;Alexis B Carter;Walter H Henricks;John M Higgins;Brian R Jackson;JiYeon Kim;Veronica E Klepeis;Long P Le;David N Louis;Diana Mandelker;Craig H Mermel;James S Michaelson;Rakesh Nagarajan;Mihae E Platt;Andrew M Quinn;Luigi Rao;Brian H Shirts;John R Gilbertson |
| Journal | annual review of materials science |
| Year | 2014 |
| DOI |
10.4103/2153-3539.126145
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.