Comparison of the levels of accuracy of an artificial neural network model and a logistic regression model for the diagnosis of acute appendicitis

Journal of Medical Systems

Volumn 31, Issue 5, 2007, Pages 357-364

  Sakai, Shinya ^a   Kobayashi, Kuriko ^a   Toyabe, Shin Ichi ^b   Mandai, Nozomu ^a   Kanda, Tatsuo ^a   Akazawa, Kohei ^b  

^a NIIGATA UNIVERSITY GRADUATE SCHOOL OF MEDICAL AND DENTAL SCIENCES   (Japan)

^b NIIGATA UNIVERSITY MEDICAL AND DENTAL HOSPITAL   (Japan)

Author keywords

Acute appendicitis; Artificial neural network; Bootstrap; Logistic regression

Indexed keywords

C REACTIVE PROTEIN;

ABDOMINAL PAIN; ACUTE ABDOMEN; ACUTE APPENDICITIS; ADOLESCENT; ADULT; AGED; ANALYTICAL ERROR; APPENDECTOMY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BODY TEMPERATURE; BOOTSTRAPPING; CHILD; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; FEMALE; HUMAN; LEUKOCYTE COUNT; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MALE; PROTEIN BLOOD LEVEL; RECEIVER OPERATING CHARACTERISTIC; SURGICAL TECHNIQUE; VALIDATION PROCESS;

ACUTE DISEASE; ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; APPENDICITIS; CHILD; CHILD, PRESCHOOL; DIAGNOSIS, DIFFERENTIAL; FEMALE; HUMANS; LOGISTIC MODELS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER);

EID: 34548068067     PISSN: 01485598     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10916-007-9077-9     Document Type: Article

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