Prospective internal validation of mathematical models to predict malignancy in adnexal masses: Results from the international ovarian tumor analysis study

Clinical Cancer Research

Volumn 15, Issue 2, 2009, Pages 684-691

  Van Holsbeke, Caroline ^a,c   Van Calster, Ben ^b   Testa, Antonia C ^d   Domali, Ekaterini ^a   Lu, Chuan ^e   Van Huffel, Sabine ^b   Valentin, Lil ^f   Timmerman, Dirk ^a  

^a UNIVERSITY HOSPITALS LEUVEN   (Belgium)

^b UNIVERSITY OF LEUVEN   (Belgium)

^c DEPARTMENT OF CARDIOLOGY   (Belgium)

^d CATHOLIC UNIVERSITY   (Italy)

^e ABERYSTWYTH UNIVERSITY   (United Kingdom)

^f LUND UNIVERSITY HOSPITAL   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ADNEXA DISEASE; ADNEXA MASS; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER CLASSIFICATION; CANCER RISK; CONTROLLED STUDY; FEMALE; HISTOPATHOLOGY; HUMAN; MAJOR CLINICAL STUDY; MALIGNANT NEOPLASTIC DISEASE; MATHEMATICAL MODEL; OUTCOME ASSESSMENT; PATTERN RECOGNITION; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; TRANSVAGINAL ECHOGRAPHY; UTERUS TUMOR; VALIDATION STUDY;

ADNEXAL DISEASES; ADULT; AREA UNDER CURVE; BAYES THEOREM; FEMALE; HUMANS; MIDDLE AGED; MODELS, THEORETICAL; OVARIAN NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; PROSPECTIVE STUDIES; REGRESSION ANALYSIS; SENSITIVITY AND SPECIFICITY;

EID: 59449107079     PISSN: 10780432     EISSN: None     Source Type: Journal    
DOI: 10.1158/1078-0432.CCR-08-0113     Document Type: Article

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