Comparison of diagnostic usefulness of predictive models in preliminary differentiation of adnexal masses

International Journal of Gynecological Cancer

Volumn 16, Issue 1, 2006, Pages 45-51

  Moszynski, R ^a   Szpurek, D ^a   Smolen, A ^b   Sajdak, S ^a  

^a POZNAN UNIVERSITY OF MEDICAL SCIENCES   (Poland)

^b MARIA CURIE SK ODOWSKA UNIVERSITY   (Poland)

Author keywords

Artificial neural network; Diagnosis; Logistic regression; Ovarian cancer

Indexed keywords

ADNEXA DISEASE; ADOLESCENT; ADULT; AGED; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BODY MASS; CANCER DIAGNOSIS; DIAGNOSTIC ACCURACY; DOPPLER FLOWMETRY; ECHOGRAPHY; FEMALE; HUMAN; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MEDICAL EXAMINATION; MENOPAUSE; OVARY CANCER; OVARY TUMOR; PARAMETER; PRIORITY JOURNAL; PROGNOSIS; RECEIVER OPERATING CHARACTERISTIC; SCHOOL CHILD; SENSITIVITY AND SPECIFICITY; STATISTICAL SIGNIFICANCE; UTERUS TUMOR;

ADULT; AGE FACTORS; AGED; CARCINOMA; DIAGNOSIS, DIFFERENTIAL; EARLY DIAGNOSIS; FEMALE; HUMANS; LOGISTIC MODELS; MIDDLE AGED; NEOPLASM STAGING; NEURAL NETWORKS (COMPUTER); OVARIAN NEOPLASMS; PREDICTIVE VALUE OF TESTS; PROGNOSIS; RISK FACTORS; ROC CURVE; SENSITIVITY AND SPECIFICITY; SURVIVAL RATE;

EID: 33645359489     PISSN: 1048891X     EISSN: 15251438     Source Type: Journal    
DOI: 10.1111/j.1525-1438.2006.00277.x     Document Type: Article

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