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Ewout W. Steyerberg
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2020 – today
- 2024
- [j20]Marieke M. van Buchem
, Anne A. H. de Hond, Claudio Fanconi, Vaibhavi B. Shah, Max Schüssler, Ilse M. J. Kant, Ewout W. Steyerberg, Tina Hernandez-Boussard
Applying natural language processing to patient messages to identify depression concerns in cancer patients. J. Am. Medical Informatics Assoc. 31(10): 2255-2262 (2024) - 2023
- [j19]Shubhayu Bhattacharyay
Mining the contribution of intensive care clinical course to outcome after traumatic brain injury. npj Digit. Medicine 6 (2023) - [j18]Anne A. H. de Hond
Perspectives on validation of clinical predictive algorithms. npj Digit. Medicine 6 (2023) - [j17]Alexandros Rekkas
A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases. npj Digit. Medicine 6 (2023) - [c5]Siri Lise van der Meijden
Identifying and Predicting Postoperative Infections Based on Readily Available Electronic Health Record Data. MIE 2023: 348-349 - [c4]Anne De Hond, Marieke M. van Buchem
Predicting Depression Risk in Patients with Cancer Using Multimodal Data. MIE 2023: 817-818 - [i2]Shubhayu Bhattacharyay
Contribution of clinical course to outcome after traumatic brain injury: mining patient trajectories from European intensive care unit data. CoRR abs/2303.04630 (2023) - 2022
- [j16]Anne De Hond, Ben Van Calster, Ewout W. Steyerberg:
Commentary: Artificial Intelligence and Statistics: Just the Old Wine in New Wineskins? Frontiers Digit. Health 4: 923944 (2022) - [j15]Marieke M. van Buchem
Analyzing patient experiences using natural language processing: development and validation of the artificial intelligence patient reported experience measure (AI-PREM). BMC Medical Informatics Decis. Mak. 22(1): 183 (2022) - [j14]Anne A. H. de Hond, Artuur M. Leeuwenberg
Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review. npj Digit. Medicine 5 (2022) - [c3]Anne De Hond, Ilse M. J. Kant, Mattia Fornasa, Giovanni Cinà, Paul W. G. Elbers, Patrick Thoral, M. Sesmu Arbous, Ewout W. Steyerberg:
Predicting readmission or death after discharge from the ICU: External validation and retraining of a machine learning model. AMIA 2022 - [i1]Shubhayu Bhattacharyay
The leap to ordinal: functional prognosis after traumatic brain injury using artificial intelligence. CoRR abs/2202.04801 (2022) - 2021
- [j13]Anne De Hond
Machine learning for developing a prediction model of hospital admission of emergency department patients: Hype or hope? Int. J. Medical Informatics 152: 104496 (2021) - [j12]Anne De Hond, Wouter Raven
Prediction of hospital admission from the emergency department: Clinician involvement, intended use, and interpretability. Int. J. Medical Informatics 155: 104585 (2021) - [j11]Marieke M. van Buchem
The digital scribe in clinical practice: a scoping review and research agenda. npj Digit. Medicine 4 (2021) - [c2]Anne A. H. de Hond, Esmee Stoop, Nicole van Keulen, Loes van Winden, Ellen Poorter, Douwe Atsma, Ilse M. J. Kant, Ewout W. Steyerberg:
Development and Validation of a Machine Learning Model to Predict Contact Moments in Post-Myocardial Infarction Home Measurements. AMIA 2021 - [c1]Hendrikus J. A. van Os, Jos P. Kanning, Marieke J. H. Wermer, Niels H. Chavannes, Mattijs E. Numans, Ynte M. Ruigrok, Erik W. van Zwet, Ewout W. Steyerberg, Hein Putter, Rolf H. H. Groenwold:
Developing clinical prediction models using primary care electronic health record data - the impact of methodological choices on model performance. AMIA 2021 - 2020
- [j10]Simone A. Cammel
How to automatically turn patient experience free-text responses into actionable insights: a natural language programming (NLP) approach. BMC Medical Informatics Decis. Mak. 20(1): 97 (2020) - [j9]Hassan Saadati
Iranian general populations' and health care providers' preferences for benefits and harms of statin therapy for primary prevention of cardiovascular disease. BMC Medical Informatics Decis. Mak. 20(1): 288 (2020) - [j8]Katya Mauff
Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach. Stat. Comput. 30(4): 999-1014 (2020)
2010 – 2019
- 2019
- [j7]Ben Van Calster
Predictive analytics in health care: how can we know it works? J. Am. Medical Informatics Assoc. 26(12): 1651-1654 (2019) - 2018
- [j6]Ellen G. Engelhardt
Inventory of oncologists' unmet needs for tools to support decision-making about palliative treatment for metastatic colorectal cancer. BMC Medical Informatics Decis. Mak. 18(1): 132:1-132:7 (2018) - 2017
- [j5]Domino Determann, Mattijs S. Lambooij, Dorte Gyrd-Hansen, Esther W. de Bekker-Grob, Ewout W. Steyerberg, Marcel Heldoorn
Personal health records in the Netherlands: potential user preferences quantified by a discrete choice experiment. J. Am. Medical Informatics Assoc. 24(3): 529-536 (2017) - [j4]Dóra Révész
Decision support systems for incurable non-small cell lung cancer: a systematic review. BMC Medical Informatics Decis. Mak. 17(1): 144:1-144:12 (2017) - 2015
- [j3]Andreas N. Strobl, Andrew J. Vickers
Improving patient prostate cancer risk assessment: Moving from static, globally-applied to dynamic, practice-specific risk calculators. J. Biomed. Informatics 56: 87-93 (2015)
2000 – 2009
- 2008
- [j2]Jolt Roukema, Ewout W. Steyerberg
Research Paper: Randomized Trial of a Clinical Decision Support System: Impact on the Management of Children with Fever without Apparent Source. J. Am. Medical Informatics Assoc. 15(1): 107-113 (2008) - [j1]Merel R. van Dijk, Ewout W. Steyerberg
A decision-analytic approach to define poor prognosis patients: a case study for non-seminomatous germ cell cancer patients. BMC Medical Informatics Decis. Mak. 8: 1 (2008)
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