Background Accurate identification of ovarian cancer (OC) is of paramount importance in
clinical treatment success. Artificial intelligence (AI) is a potentially reliable assistant for the …

Foreword This Journal feature begins with a case vignette highlighting a common clinical
problem. Evidence supporting various strategies is then presented, followed by a review of …

Objectives To prospectively assess the diagnostic performance of simple ultrasound rules to
predict benignity/malignancy in an adnexal mass and to test the performance of the risk of …

The combined factors of the leadership demands of globalization on firms, firms' responses
to those demands, and social scientists' efforts to investigate global leadership spawned a …

Ovarian cancer is characterize by few early symptoms, presentation at an advanced stage,
and poor survival. As a result, it is the most frequent cause of death from gynecological …

Purpose To collect data for the development of a more universally useful logistic regression
model to distinguish between a malignant and benign adnexal tumor before surgery …

BACKGROUND Characterizing ovarian pathology is fundamental to optimizing
management in both pre-and post-menopausal women. Inappropriate referral to oncology …

The present study considered the reliability and validity of the 78-item revised version of the
Multicultural Personality Questionnaire, a multidimensional instrument aimed at measuring …

The present study investigates the link between multilingualism/multiculturalism,
acculturation and the personality profile (as measured by the Multicultural Personality …

In order to ensure that ovarian cancer patients access appropriate treatment to improve the
outcome of this disease, accurate characterization before any surgery on ovarian pathology …