A Machine Learning Approach for Identifying Anatomical Locations of Actionable Findings in Radiology Reports

Recognizing the anatomical location of actionable findings in radiology reports is an important part of the communication of critical test results between caregivers. One of the difficulties of identifying anatomical locations of actionable findings stems from the fact that anatomical locations are...

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Detaylı Bibliyografya
Asıl Yazarlar: Roberts, Kirk, Rink, Bryan, Harabagiu, Sanda M., Scheuermann, Richard H., Toomay, Seth, Browning, Travis, Bosler, Teresa, Peshock, Ronald
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: American Medical Informatics Association 2012
Konular:
Articles
Online Erişim:https://ncbi.nlm.nih.gov/pmc/articles/PMC3540484/
https://ncbi.nlm.nih.gov/pubmed/23304352
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