000 01658 a2200457 4500
005 20250518025312.0
264 0 _c20200619
008 202006s 0 0 eng d
022 _a1558-349X
024 7 _a10.1016/j.jacr.2018.12.004
_2doi
040 _aNLM
_beng
_cNLM
100 1 _aBrown, A D
245 0 0 _aNatural Language Processing of Radiology Reports in Patients With Hepatocellular Carcinoma to Predict Radiology Resource Utilization.
_h[electronic resource]
260 _bJournal of the American College of Radiology : JACR
_cJun 2019
300 _a840-844 p.
_bdigital
500 _aPublication Type: Journal Article
650 0 4 _aAged
650 0 4 _aArea Under Curve
650 0 4 _aCarcinoma, Hepatocellular
_xdiagnostic imaging
650 0 4 _aDatabases, Factual
650 0 4 _aFemale
650 0 4 _aHealth Resources
_xstatistics & numerical data
650 0 4 _aHumans
650 0 4 _aLiver Neoplasms
_xdiagnostic imaging
650 0 4 _aMachine Learning
_xeconomics
650 0 4 _aMale
650 0 4 _aMiddle Aged
650 0 4 _aNatural Language Processing
650 0 4 _aOntario
650 0 4 _aPredictive Value of Tests
650 0 4 _aROC Curve
650 0 4 _aRadiology Department, Hospital
650 0 4 _aRadiology Information Systems
650 0 4 _aResearch Report
650 0 4 _aRetrospective Studies
650 0 4 _aSensitivity and Specificity
650 0 4 _aTomography, X-Ray Computed
_xeconomics
700 1 _aKachura, J R
773 0 _tJournal of the American College of Radiology : JACR
_gvol. 16
_gno. 6
_gp. 840-844
856 4 0 _uhttps://doi.org/10.1016/j.jacr.2018.12.004
_zAvailable from publisher's website
999 _c29440229
_d29440229