Laure Wynants

12.8k total citations · 3 hit papers
72 papers, 3.6k citations indexed

About

Laure Wynants is a scholar working on Obstetrics and Gynecology, Reproductive Medicine and Epidemiology. According to data from OpenAlex, Laure Wynants has authored 72 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Obstetrics and Gynecology, 16 papers in Reproductive Medicine and 13 papers in Epidemiology. Recurrent topics in Laure Wynants's work include Endometrial and Cervical Cancer Treatments (15 papers), Ovarian cancer diagnosis and treatment (13 papers) and Health Systems, Economic Evaluations, Quality of Life (11 papers). Laure Wynants is often cited by papers focused on Endometrial and Cervical Cancer Treatments (15 papers), Ovarian cancer diagnosis and treatment (13 papers) and Health Systems, Economic Evaluations, Quality of Life (11 papers). Laure Wynants collaborates with scholars based in Belgium, Netherlands and United Kingdom. Laure Wynants's co-authors include Ben Van Calster, Ewout W. Steyerberg, Maarten van Smeden, D. Timmerman, David J. McLernon, Jan Y. Verbakel, Andrew J. Vickers, T. Bourne, Evangelia Christodoulou and Monique J. Roobol and has published in prestigious journals such as SHILAP Revista de lepidopterología, Clinical Cancer Research and American Journal of Obstetrics and Gynecology.

In The Last Decade

Laure Wynants

65 papers receiving 3.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Calibration: the Achilles heel of predictive analytics

2019 910 citations Ben Van Calster, David J. McLernon et al. BMC Medicine profile →
Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

2018 723 citations Ben Van Calster, Laure Wynants et al. European Urology profile →
There is no such thing as a validated prediction model

2023 117 citations Ben Van Calster, Ewout W. Steyerberg et al. BMC Medicine profile →

Peers

Countries citing papers authored by Laure Wynants

Since Specialization

Citations

This map shows the geographic impact of Laure Wynants's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Laure Wynants with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laure Wynants more than expected).

Fields of papers citing papers by Laure Wynants

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laure Wynants. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Laure Wynants. The network helps show where Laure Wynants may publish in the future.

Co-authorship network of co-authors of Laure Wynants

This figure shows the co-authorship network connecting the top 25 collaborators of Laure Wynants. A scholar is included among the top collaborators of Laure Wynants based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Laure Wynants. Laure Wynants is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	Challenges and Recommendations for Electronic Health Records Data Extraction and Preparation for Dynamic Prediction Modeling in Hospitalized Patients: Practical Guide and Tutorial	Journal of Medical Internet Research	Elena Albu, Shan Gao et al.	0
2	Number of Publications on New Clinical Prediction Models: A Bibliometric Review	JMIR Medical Informatics	Banafsheh Arshi, Laure Wynants et al.	0
3	Assessing the quality of prediction models in health care using the Prediction model Risk Of Bias ASsessment Tool (PROBAST): an evaluation of its use and practical application	Journal of Clinical Epidemiology	T. K. Kaul, Johanna AAG Damen et al.	1
4	Table 0; documenting the steps to go from clinical database to research dataset	Journal of Clinical Epidemiology	Bas C. T. van Bussel, Ronny M. Schnabel et al.	4
5	Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care	European Journal of General Practice	Laure Wynants, Natascha J.H. Broers et al.	2
6	There is no such thing as a validated prediction model breakdown →	BMC Medicine	Ben Van Calster, Ewout W. Steyerberg et al.	117
7	Estimating risk of endometrial malignancy and other intracavitary uterine pathology in women without abnormal uterine bleeding using IETA‐1 multinomial regression model: validation study	Ultrasound in Obstetrics and Gynecology	Ruben Heremans, Laure Wynants et al.	1
8	The ADNEX risk prediction model for ovarian cancer diagnosis: A systematic review and meta-analysis of external validation studies	medRxiv	Paula Dhiman, Gary S. Collins et al.	2
9	Structural under-reporting of informed consent, data handling and sharing, ethical approval, and application of Open Science principles as proxies for study quality conduct in COVID-19 research: a systematic scoping review	BMJ Global Health	Walther van Mook, Josanne Cox‐Brinkman et al.	4
10	Systematic review finds risk of bias and applicability concerns for models predicting central line-associated bloodstream infection	Journal of Clinical Epidemiology	Shan Gao, Elena Albu et al.	6
11	The Risk of Endometrial Malignancy and Other Endometrial Pathology in Women with Abnormal Uterine Bleeding: An Ultrasound-Based Model Development Study by the IETA Group	Gynecologic and Obstetric Investigation	Laure Wynants, Jan Y. Verbakel et al.	7
12	Antibiotic use in ambulatory care for acutely ill children in high-income countries: a systematic review and meta-analysis	Archives of Disease in Childhood	Nhung TH Trinh, Joseph Freer et al.	20
13	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 and Gynecology	J. Farren, Maria Jalmbrant et al.	35
14	Developing risk models for multicenter data using standard logistic regression produced suboptimal predictions: A simulation study	Biometrical Journal	Ben Van Calster, D. Timmerman et al.	12
15	Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting	SHILAP Revista de lepidopterología	Laure Wynants, David M. Kent et al.	28
16	Three myths about risk thresholds for prediction models	BMC Medicine	Laure Wynants, Maarten van Smeden et al.	114
17	Random‐effects meta‐analysis of the clinical utility of tests and prediction models	Statistics in Medicine	Laure Wynants, Richard D Riley et al.	29
18	Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators breakdown →	European Urology	Ben Van Calster, Laure Wynants et al.	723
19	Clinical Utility of Risk Models to Refer Patients with Adnexal Masses to Specialized Oncology Care: Multicenter External Validation Using Decision Curve Analysis	Clinical Cancer Research	Laure Wynants, D. Timmerman et al.	37
20	Key steps and common pitfalls in developing and validating risk models	BJOG An International Journal of Obstetrics & Gynaecology	Laure Wynants, Gary S. Collins et al.	68

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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