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Natural Language Processing of Large-Scale Structured Radiology Reports to Identify Oncologic Patients With or Without Splenomegaly Over a 10-Year Period.

Simon SunKaelan LuptonKaren BatchHuy NguyenLior GazitNatalie GangaiJessica ChoKevin J NicholasFarhana ZulkernineVaradan SevilimeduAmber L SimpsonRichard Kinh Gian Do
Published in: JCO clinical cancer informatics (2022)
Automated splenomegaly labeling by NLP of radiology report demonstrates good accuracy, precision, and recall. Splenomegaly is most frequently reported in patients with leukemia, followed by patients with HB.
Keyphrases
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  • machine learning
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  • rectal cancer
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  • adverse drug
  • robot assisted