To develop a logistic regression model that can discriminate between benign and malignant adnexal masses perceived to be difficult to classify by subjective evaluation of gray-scale and Doppler ultrasound findings (subjective assessment) and to compare its diagnostic performance with that of subjective assessment, serum CA 125 and the risk of malignancy index (RMI).

Valentin, L., Ameye, L., Savelli, L., Fruscio, R., Leone, F., Czekierdowski, A., et al. (2011). Adnexal masses difficult to classify as benign or malignant using subjective assessment of gray-scale and Doppler ultrasound findings: logistic regression models do not help. ULTRASOUND IN OBSTETRICS & GYNECOLOGY, 38(4), 456-465 [10.1002/uog.9030].

Adnexal masses difficult to classify as benign or malignant using subjective assessment of gray-scale and Doppler ultrasound findings: logistic regression models do not help

FRUSCIO, ROBERT;LISSONI, ANDREA ALBERTO;
2011

Abstract

To develop a logistic regression model that can discriminate between benign and malignant adnexal masses perceived to be difficult to classify by subjective evaluation of gray-scale and Doppler ultrasound findings (subjective assessment) and to compare its diagnostic performance with that of subjective assessment, serum CA 125 and the risk of malignancy index (RMI).
Articolo in rivista - Articolo scientifico
Sensitivity and Specificity; Ultrasonography, Doppler, Color; Adnexal Diseases; Ovarian Neoplasms; Middle Aged; Female; Probability; Logistic Models; Diagnosis, Differential; Humans; Area Under Curve
English
2011
38
4
456
465
none
Valentin, L., Ameye, L., Savelli, L., Fruscio, R., Leone, F., Czekierdowski, A., et al. (2011). Adnexal masses difficult to classify as benign or malignant using subjective assessment of gray-scale and Doppler ultrasound findings: logistic regression models do not help. ULTRASOUND IN OBSTETRICS & GYNECOLOGY, 38(4), 456-465 [10.1002/uog.9030].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/29398
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