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Impact of predictor measurement heterogeneity across settings on the performance of prediction models: A measurement error perspective

Statistics in medicine, 2019-08, Vol.38 (18), p.3444-3459

2019

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A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data

Journal of clinical epidemiology, 2015-12, Vol.68 (12), p.1406-1414

2015

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Random‐effects meta‐analysis of the clinical utility of tests and prediction models

Statistics in medicine, 2018-05, Vol.37 (12), p.2034-2052

2018

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Differences in post‐traumatic stress, anxiety and depression following miscarriage or ectopic pregnancy between women and their partners: multicenter prospective cohort study

Ultrasound in obstetrics & gynecology, 2021-01, Vol.57 (1), p.141-148

2021

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Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding

Ultrasound in obstetrics & gynecology, 2021-01, Vol.57 (1), p.164-172

2021

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Diagnostic protocols for the management of pregnancy of unknown location: a systematic review and meta‐analysis

BJOG : an international journal of obstetrics and gynaecology, 2019-01, Vol.126 (2), p.190-198

2019

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

Ultrasound in obstetrics & gynecology, 2013-01, Vol.41 (1), p.9-20

2013

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Ultrasound characteristics of endometrial cancer as defined by International Endometrial Tumor Analysis (IETA) consensus nomenclature: prospective multicenter study

Ultrasound in obstetrics & gynecology, 2018-06, Vol.51 (6), p.818-828

2018

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Validation of ADNEX and IOTA two‐step strategy and estimation of risk of complications during follow‐up of adnexal masses in low‐risk population

Ultrasound in obstetrics & gynecology, 2024-09, Vol.64 (3), p.395-404

2024

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Updating M6 pregnancy of unknown location risk‐prediction model including evaluation of clinical factors

Ultrasound in obstetrics & gynecology, 2024-03, Vol.63 (3), p.408-418

2024

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Simple ultrasound‐based rules for the diagnosis of ovarian cancer

Ultrasound in obstetrics & gynecology, 2008-06, Vol.31 (6), p.681-690

2008

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Triaging women with pregnancy of unknown location using two‐step protocol including M6 model: clinical implementation study

Ultrasound in obstetrics & gynecology, 2020-01, Vol.55 (1), p.105-114

2020

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Benign descriptors and ADNEX in two‐step strategy to estimate risk of malignancy in ovarian tumors: retrospective validation in IOTA5 multicenter cohort

Ultrasound in obstetrics & gynecology, 2023-02, Vol.61 (2), p.231-242

2023

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External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study

BJOG : an international journal of obstetrics and gynaecology, 2021-02, Vol.128 (3), p.552-562

2021

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Does ignoring clustering in multicenter data influence the performance of prediction models? A simulation study

Statistical methods in medical research, 2018-06, Vol.27 (6), p.1723-1736

2018

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Early‐pregnancy events and subsequent antenatal, delivery and neonatal outcomes: prospective cohort study

Ultrasound in obstetrics & gynecology, 2019-10, Vol.54 (4), p.530-537

2019

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Ultrasound‐based risk model for preoperative prediction of lymph‐node metastases in women with endometrial cancer: model‐development study

Ultrasound in obstetrics & gynecology, 2020-09, Vol.56 (3), p.443-452

2020

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Clinical study investigating the role of lymphadenectomy, surgical castration and adjuvant hormonal treatment in endometrial stromal sarcoma

British journal of cancer, 2007-11, Vol.97 (9), p.1194-1199

2007

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External validation of ADNEX model for diagnosing ovarian cancer: evaluating performance of differentiation between tumor subgroups

Ultrasound in obstetrics & gynecology, 2017-09, Vol.50 (3), p.406-407

Van Calster, B.

2017

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Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study

BMJ (Online), 2014-10, Vol.349 (oct07 3), p.g5920-g5920

International edition, 2014

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Key steps and common pitfalls in developing and validating risk models

BJOG : an international journal of obstetrics and gynaecology, 2017-02, Vol.124 (3), p.423-432

2017

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Subjective assessment versus ultrasound models to diagnose ovarian cancer: A systematic review and meta-analysis

European journal of cancer (1990), 2016-05, Vol.58, p.17-29

2016

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Rationalizing the follow-up of pregnancies of unknown location

Human reproduction (Oxford), 2007-06, Vol.22 (6), p.1744-1750

2007

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OP03.02: Artificial intelligence applied to ultrasound diagnosis of pelvic gynecological tumours: a systematic scoping review and meta‐analysis

Ultrasound in obstetrics & gynecology, 2024-09, Vol.64 (S1), p.65-65

2024

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Impact of Medical Device Regulation on use of ultrasound-based prediction models in clinical practice

Ultrasound in obstetrics & gynecology, 2024-05

2024

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Impact of predictor measurement heterogeneity across settings on the performance of prediction models: A measurement error perspective

A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data

Random‐effects meta‐analysis of the clinical utility of tests and prediction models

Differences in post‐traumatic stress, anxiety and depression following miscarriage or ectopic pregnancy between women and their partners: multicenter prospective cohort study

Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding

Diagnostic protocols for the management of pregnancy of unknown location: a systematic review and meta‐analysis

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

Ultrasound characteristics of endometrial cancer as defined by International Endometrial Tumor Analysis (IETA) consensus nomenclature: prospective multicenter study

Validation of ADNEX and IOTA two‐step strategy and estimation of risk of complications during follow‐up of adnexal masses in low‐risk population

Updating M6 pregnancy of unknown location risk‐prediction model including evaluation of clinical factors

Simple ultrasound‐based rules for the diagnosis of ovarian cancer

Triaging women with pregnancy of unknown location using two‐step protocol including M6 model: clinical implementation study

Benign descriptors and ADNEX in two‐step strategy to estimate risk of malignancy in ovarian tumors: retrospective validation in IOTA5 multicenter cohort

External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study

Does ignoring clustering in multicenter data influence the performance of prediction models? A simulation study

Early‐pregnancy events and subsequent antenatal, delivery and neonatal outcomes: prospective cohort study

Ultrasound‐based risk model for preoperative prediction of lymph‐node metastases in women with endometrial cancer: model‐development study

Clinical study investigating the role of lymphadenectomy, surgical castration and adjuvant hormonal treatment in endometrial stromal sarcoma

External validation of ADNEX model for diagnosing ovarian cancer: evaluating performance of differentiation between tumor subgroups

Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study

Key steps and common pitfalls in developing and validating risk models

Subjective assessment versus ultrasound models to diagnose ovarian cancer: A systematic review and meta-analysis

Rationalizing the follow-up of pregnancies of unknown location

OP03.02: Artificial intelligence applied to ultrasound diagnosis of pelvic gynecological tumours: a systematic scoping review and meta‐analysis

Impact of Medical Device Regulation on use of ultrasound-based prediction models in clinical practice

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