Laure Wynants
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Laure Wynantsmathematics Degrees
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Laure Wynants's Degrees
- PhD Statistics University of Amsterdam
- Masters Epidemiology University of Antwerp
- Bachelors Biomedical Sciences University of Antwerp
Why Is Laure Wynants Influential?
(Suggest an Edit or Addition)According to Wikipedia, Laure Wynants is a Belgian epidemiologist who is a professor at Maastricht University. She studies prediction models in medicine and hospital acquired infections. Early life and education Wynants studied biostatistics at KU Leuven in Belgium. She remained there for her doctoral research, where she focused on prediction models. Her doctorate sought to predict whether ovarian tumours are benign or malignant, and how likely it is that the insertion of a catheter will cause bloodstream infection.
Laure Wynants's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal (2020) (1757)
- Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal (2020) (748)
- Calibration: the Achilles heel of predictive analytics (2019) (494)
- Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators. (2018) (401)
- Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group. (2016) (200)
- The impact of complaints procedures on the welfare, health and clinical practise of 7926 doctors in the UK: a cross-sectional survey (2015) (164)
- Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection (2020) (107)
- Strategies to diagnose ovarian cancer: new evidence from phase 3 of the multicentre international IOTA study (2014) (98)
- Multicentre external validation of IOTA prediction models and RMI by operators with varied training (2013) (95)
- A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data. (2015) (89)
- Risk of complications in patients with conservatively managed ovarian tumours (IOTA5): a 2-year interim analysis of a multicentre, prospective, cohort study. (2019) (80)
- Predictive analytics in health care: how can we know it works? (2019) (75)
- Practical guidance for applying the ADNEX model from the IOTA group to discriminate between different subtypes of adnexal tumors (2015) (73)
- Three myths about risk thresholds for prediction models (2019) (73)
- Key steps and common pitfalls in developing and validating risk models (2017) (70)
- Predicting successful vaginal birth after Cesarean section using a model based on Cesarean scar features examined by transvaginal sonography (2013) (57)
- Post-traumatic stress, anxiety and depression following miscarriage and ectopic pregnancy: a multi-center, prospective, cohort study. (2019) (53)
- Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study (2020) (50)
- Does the presence of a Caesarean section scar affect implantation site and early pregnancy outcome in women attending an early pregnancy assessment unit? (2013) (49)
- Doctors' experiences and their perception of the most stressful aspects of complaints processes in the UK: an analysis of qualitative survey data (2016) (46)
- Methodology over metrics: current scientific standards are a disservice to patients and society (2021) (43)
- Clinical Utility of Risk Models to Refer Patients with Adnexal Masses to Specialized Oncology Care: Multicenter External Validation Using Decision Curve Analysis (2017) (33)
- Doctors’ perception of support and the processes involved in complaints investigations and how these relate to welfare and defensive practice: a cross-sectional survey of the UK physicians (2017) (32)
- Validation of the Performance of International Ovarian Tumor Analysis (IOTA) Methods in the Diagnosis of Early Stage Ovarian Cancer in a Non-Screening Population (2017) (29)
- Changing predictor measurement procedures affected the performance of prediction models in clinical examples. (2019) (28)
- Random‐effects meta‐analysis of the clinical utility of tests and prediction models (2018) (27)
- Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding (2020) (27)
- Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting (2019) (24)
- Does ignoring clustering in multicenter data influence the performance of prediction models? A simulation study (2018) (24)
- ROC curves for clinical prediction models part 1: ROC plots showed no added value above the AUC when evaluating the performance of clinical prediction models. (2020) (22)
- Validation of ultrasound strategies to assess tumor extension and to predict high‐risk endometrial cancer in women from the prospective IETA (International Endometrial Tumor Analysis)‐4 cohort (2020) (21)
- Screening for data clustering in multicenter studies: the residual intraclass correlation (2013) (21)
- Differences in post‐traumatic stress, anxiety and depression following miscarriage or ectopic pregnancy between women and their partners: multicenter prospective cohort study (2020) (16)
- Covipendium: Information available to support the development of medical countermeasures and interventions against COVID-19 (2020) (14)
- Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis (2022) (13)
- ROC curves for clinical prediction models: from waste of ink towards useful insight? (2020) (12)
- Machine Learning in Medicine. (2019) (10)
- Ultrasound‐based risk model for preoperative prediction of lymph‐node metastases in women with endometrial cancer: model‐development study (2019) (10)
- Developing risk models for multicenter data using standard logistic regression produced suboptimal predictions: A simulation study (2020) (9)
- Improving clinical management of COVID-19: the role of prediction models (2021) (9)
- Demystifying AI in healthcare (2020) (9)
- External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study (2020) (7)
- Assessing Performance and Clinical Usefulness in Prediction Models With Survival Outcomes: Practical Guidance for Cox Proportional Hazards Models (2022) (6)
- Methods for Evaluating Medical Tests and Biomarkers (2017) (3)
- Erratum to "ROC curves for clinical prediction models part 1. ROC plots showed no added value above the AUC when evaluating the performance of clinical prediction models" [J Clin Epidemiol. 126C(2020):207-16]. (2020) (3)
- OC01.01: Risk of complications in conservatively managed adnexal masses initially thought to be benign at subjective impression by the ultrasound examiner (2017) (3)
- Benign descriptors and ADNEX in two‐step strategy to estimate risk of malignancy in ovarian tumors: retrospective validation in IOTA5 multicenter cohort (2022) (3)
- ROC curves for clinical prediction models part 3: The ROC plot: a picture that needs a 1000 words. (2020) (3)
- Ultrasound features of endometrial pathology in women without abnormal uterine bleeding: results from the International Endometrial Tumor Analysis study (IETA3) (2022) (3)
- IPD Meta‐Analysis for Clinical Prediction Model Research (2021) (2)
- Prediction models in multicenter studies: methodological aspects and current state of the art (2015) (2)
- 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 (2022) (2)
- Adherence rates to a prediction tool identifying women with an increased gestational diabetes risk: An implementation study (2020) (1)
- Does poor methodological quality of prediction modeling studies translate to poor model performance? An illustration in traumatic brain injury (2022) (1)
- Clinical Risk Prediction Models based on Multicenter Data: Methods for Model Development and Validation (2016) (1)
- Minimal reporting improvement after peer review in reports of COVID-19 prediction models: systematic review (2022) (1)
- Antibiotic use in ambulatory care for acutely ill children in high-income countries: a systematic review and meta-analysis (2022) (1)
- The independent effect of tumor size in predicting ovarian malignancy. (2012) (1)
- OC01.02: Balancing risks of surgery with risks of conservative management of benign adnexal masses: results from the postmenopausal follow‐up arm of IOTA5 (2018) (1)
- Predicting COVID-19 prognosis in the ICU remained challenging: external validation in a multinational regional cohort (2022) (1)
- EVALUATING THE CLINICAL UTILITY OF PREDICTION MODELS IN A HETEROGENEOUS MULTICENTER POPULATION USING DECISION-ANALYTIC MEASURES: THE RANDOM EFFECTS-WEIGHTED NET BENEFIT (2014) (0)
- OC12.06: Validation of objective measurements to predict myometrial or cervical stromal invasion and prediction models to predict high‐risk endometrial cancer (2018) (0)
- Prediction models: stepwise development and simultaneous validation is a step back. (2021) (0)
- A systematic review of risk prediction models for central line-associated bloodstream infection (CLA-BSI) in hospitalized patients. (2023) (0)
- OC11.03: Prospective validation of IOTA methods in the differentiation between benign and malignant adnexal masses (2017) (0)
- cross-sectional survey of the UK physicians welfare and defensive practice : a investigations and how these relate to processes involved in complaints Doctors ' perception of support and the Audenhove (2017) (0)
- Dataset for: Random-effects meta-analysis of the clinical utility of tests and prediction models (2018) (0)
- A systematic review of risk prediction models for central line-associated bloodstream infection (CLA-BSI) in hospitalized patients (Scopus). (2023) (0)
- Value of Information Analysis for External Validation of Risk Prediction Models (2022) (0)
- A systematic review of risk prediction models for central line-associated bloodstream infection (CLA-BSI) in hospitalized patients (Web of Science Core Collection). (2023) (0)
- 28th World Congress on Ultrasound in Obstetrics and Gynecology, 20–24 October 2018, Singapore: presentations and awards (2018) (0)
- Correction (1999) (0)
- OC12.01: Reporting the endometrium and intracavitary lesions using the IETA terminology: results of the IETA‐1 multicentric prospective study (2018) (0)
- Reply (2013) (0)
- OC08.03: Subjective and objective strategies to assess myometrial invasion and cervical stromal invasion in women with endometrial cancer from the IETA cohort (2018) (0)
- OC07.01: The International Endometrial Tumor Analysis (IETA) study: interim analysis of measurement differences between centres (2015) (0)
- Risk of endometrial cancer in asymptomatic postmenopausal women in relation to ultrasonographic endometrial thickness. (2023) (0)
- 27th World Congress on Ultrasound in Obstetrics and Gynecology, 16–19 September 2017, Vienna, Austria: presentations and awards (2017) (0)
- OC08.02: A preoperative risk model with ultrasound variables to assess lymph node metastasis in endometrial cancer patients: a model development and validation study by the IETA group (2018) (0)
- Risk assessment for endometrial cancer in women with abnormal vaginal bleeding: Results from the prospective IETA‐1 cohort study (2022) (0)
- VP66.25: Triaging women with abnormal uterine bleeding in ambulatory care: results from the prospective IETA‐1 cohort study (2020) (0)
- Systematic review of prediction models for triaging cov-19 patients (2020) (0)
- There is no such thing as a validated prediction model (2023) (0)
- OC16.04: External validation of the M6 model and the two‐step triage system for pregnancies of unknown location (2019) (0)
- The M6 risk prediction model and two-step strategy to characterize pregnancies of unknown location: a multicentre external validation study (2020) (0)
- OC12.02: A comparison of demographic characteristics between women with benign and malignant endometrium: results of the IETA‐1 multicentre prospective study (2018) (0)
- Reply: To PMID 23371440. (2013) (0)
- A systematic review of risk prediction models for central line-associated bloodstream infection (CLA-BSI) in hospitalized patients (Embase). (2023) (0)
- Erratum to: Methods for evaluating medical tests and biomarkers (2017) (0)
- OC11.01: Clinical utility of IOTA models, RMI and ROMA to refer patients with adnexal masses to specialised oncology care (2017) (0)
- The number of events per variable needed to develop risk prediction models from clustered data using multilevel modeling: a simulation study (2011) (0)
- OC12.03: An ultrasound‐based algorithm to determine the likelihood of various causes of abnormal uterine bleeding: a proposal by the IETA group (2018) (0)
- Clinical utility of prediction models for ovarian tumor diagnosis: a decision curve analysis (2016) (0)
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