Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies

J Kaijser, T Bourne, L Valentin… - … in obstetrics & …, 2013 - Wiley Online Library
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 …

Ultrasound scanning of the pelvis and abdomen for staging of gynecological tumors: a review

D Fischerova - Ultrasound in obstetrics & gynecology, 2011 - Wiley Online Library
This Review documents examination techniques, sonographic features and clinical
considerations in ultrasound assessment of gynecological tumors. The methodology of …

Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and …

B Van Calster, K Van Hoorde, L Valentin, AC Testa… - Bmj, 2014 - bmj.com
Objectives To develop a risk prediction model to preoperatively discriminate between
benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian …

Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group

D Timmerman, B Van Calster, A Testa, L Savelli… - American journal of …, 2016 - Elsevier
Background Accurate methods to preoperatively characterize adnexal tumors are pivotal for
optimal patient management. A recent metaanalysis concluded that the International …

Simple ultrasound rules to distinguish between benign and malignant adnexal masses before surgery: prospective validation by IOTA group

D Timmerman, L Ameye, D Fischerova, E Epstein… - Bmj, 2010 - bmj.com
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 …

Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study

B Van Calster, L Valentin, W Froyman, C Landolfo… - Bmj, 2020 - bmj.com
Objective To evaluate the performance of diagnostic prediction models for ovarian
malignancy in all patients with an ovarian mass managed surgically or conservatively …

Artificial intelligence and machine learning in cancer research: a systematic and thematic analysis of the top 100 cited articles indexed in Scopus database

IH Musa, LO Afolabi, I Zamit, TH Musa… - Cancer …, 2022 - journals.sagepub.com
Introduction Cancer is a major public health problem and a global leading cause of death
where the screening, diagnosis, prediction, survival estimation, and treatment of cancer and …

[HTML][HTML] Validation of a second-generation multivariate index assay for malignancy risk of adnexal masses

RL Coleman, TJ Herzog, DW Chan, DG Munroe… - American journal of …, 2016 - Elsevier
Background Women with adnexal mass suspected of ovarian malignancy are likely to
benefit from consultation with a gynecologic oncologist, but imaging and biomarker tools to …

Evaluating the risk of ovarian cancer before surgery using the ADNEX model: a multicentre external validation study

A Sayasneh, L Ferrara, B De Cock, S Saso… - British journal of …, 2016 - nature.com
Background: The International Ovarian Tumour Analysis (IOTA) group have developed the
ADNEX (The Assessment of Different NEoplasias in the adneXa) model to predict the risk …

A perspective on ovarian cancer biomarkers: past, present and yet-to-come

FR Ueland - Diagnostics, 2017 - mdpi.com
The history of biomarkers and ultrasonography dates back over more than 50 years. The
present status of biomarkers used in the context of ovarian cancer is addressed. Attention is …