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Paper Details

Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.
Acad Emerg Med
29
2016
ED, KD, Kawasaki Disease, Kawasaki disease, Patients, cardiac, children, febrile illness, fever, patients
Child, Data Mining, Electronic Health Records, Emergency Service, Hospital, Humans, Mucocutaneous Lymph Node Syndrome, Natural Language Processing, Sensitivity and Specificity
Author NameAffiliation
Son DoanUniversity of California
Cleo K MaeharaUniversity of California
Cleo K MaeharaUniversity of California
Juan D ChaparroUniversity of California
Sisi LuUniversity of Pittsburgh
Ruiling LiuThe University of Texas Health Science Center at Houston
Ruiling LiuThe University of Texas Health Science Center at Houston
Amanda Graham
Erika BerryUniversity of California at San Diego
Chun-Nan HsuUniversity of California
Chun-Nan HsuUniversity of California
John T KanegayeUniversity of California at San Diego
John T KanegayeRady Children's Hospital San Diego
David Lloyd
David LloydEmory University School of Medicine
Lucila Ohno-MachadoUniversity of California
Lucila Ohno-MachadoUniversity of California
Jane C BurnsUniversity of California at San Diego
Jane C BurnsRady Children's Hospital San Diego
Adriana H TremouletUniversity of California at San Diego
Adriana H TremouletRady Children's Hospital San Diego
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Release 1.2