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Ben van Calster

Showing results (211-220 of 224) with videos related to

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JAMA Oncology|December 15, 2022
External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk GroupsStefan Timmerman, Lil Valentin, Jolien Ceusters, et al.
Iscience|November 10, 2025
Added value of serum proteins to clinical and ultrasound information in predicting the risk of malignancy in ovarian tumorsAn Coosemans, Jolien Ceusters, Chiara Landolfo, et al.
The Lancet. Oncology|February 4, 2018
Oncological management and obstetric and neonatal outcomes for women diagnosed with cancer during pregnancy: a 20-year international cohort study of 1170 patientsJorine de Haan, Magali Verheecke, Kristel Van Calsteren, et al.
BMJ (Clinical Research Ed.)|August 1, 2020
Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort studyBen Van Calster, Lil Valentin, Wouter Froyman, et al.
The Lancet. Oncology|February 10, 2019
Risk of complications in patients with conservatively managed ovarian tumours (IOTA5): a 2-year interim analysis of a multicentre, prospective, cohort studyWouter Froyman, Chiara Landolfo, Bavo De Cock, et al.
BMJ (Clinical Research Ed.)|March 24, 2025
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methodsKarel G M Moons, Johanna A A Damen, Tabea Kaul, et al.
Ewha Medical Journal|July 31, 2025
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translationGary S Collins, Karel G M Moons, Paula Dhiman, et al.
BMJ (Clinical Research Ed.)|April 16, 2024
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methodsGary S Collins, Karel G M Moons, Paula Dhiman, et al.
BMJ (Clinical Research Ed.)|July 12, 2022
Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysisValentijn M T de Jong, Rebecca Z Rousset, Neftalí Eduardo Antonio-Villa, et al.
BMJ (Clinical Research Ed.)|April 9, 2020
Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisalLaure Wynants, Ben Van Calster, Gary S Collins, et al.
Pageof 23

Showing results (211-220 of 224) with videos related to

Sort By:
Pageof 23
JAMA Oncology|December 15, 2022
External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk GroupsStefan Timmerman, Lil Valentin, Jolien Ceusters, et al.
Iscience|November 10, 2025
Added value of serum proteins to clinical and ultrasound information in predicting the risk of malignancy in ovarian tumorsAn Coosemans, Jolien Ceusters, Chiara Landolfo, et al.
The Lancet. Oncology|February 4, 2018
Oncological management and obstetric and neonatal outcomes for women diagnosed with cancer during pregnancy: a 20-year international cohort study of 1170 patientsJorine de Haan, Magali Verheecke, Kristel Van Calsteren, et al.
BMJ (Clinical Research Ed.)|August 1, 2020
Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort studyBen Van Calster, Lil Valentin, Wouter Froyman, et al.
The Lancet. Oncology|February 10, 2019
Risk of complications in patients with conservatively managed ovarian tumours (IOTA5): a 2-year interim analysis of a multicentre, prospective, cohort studyWouter Froyman, Chiara Landolfo, Bavo De Cock, et al.
BMJ (Clinical Research Ed.)|March 24, 2025
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methodsKarel G M Moons, Johanna A A Damen, Tabea Kaul, et al.
Ewha Medical Journal|July 31, 2025
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods: a Korean translationGary S Collins, Karel G M Moons, Paula Dhiman, et al.
BMJ (Clinical Research Ed.)|April 16, 2024
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methodsGary S Collins, Karel G M Moons, Paula Dhiman, et al.
BMJ (Clinical Research Ed.)|July 12, 2022
Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysisValentijn M T de Jong, Rebecca Z Rousset, Neftalí Eduardo Antonio-Villa, et al.
BMJ (Clinical Research Ed.)|April 9, 2020
Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisalLaure Wynants, Ben Van Calster, Gary S Collins, et al.
Pageof 23