Ben Van Calster

27 papers B 3Journal 19Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Calibration in Multiple Instance Learning: Evaluating Aggregation Methods for Ultrasound-Based Diagnosis. MICCAI (15) Axel Geysels, Ben Van Calster, Bart De Moor, Wouter Froyman, Dirk Timmerman
2025	J	`jnl`	Challenges and recommendations for Electronic Health Records data extraction and preparation for dynamic prediction modelling in hospitalized patients - a practical guide. CoRR Elena Albu, Shan Gao, Pieter Stijnen, Frank E. Rademakers, Bas C. T. van Bussel, Taya Collyer, Tina Hernandez-Boussard, Laure Wynants, Ben Van Calster
2025	J	`jnl`	Critical Appraisal of Fairness Metrics in Clinical Predictive AI. CoRR João Matos, Ben Van Calster, Leo Anthony Celi, Paula Dhiman, Judy Wawira Gichoya, Richard D. Riley, Chris Russell, Sara Khalid, Gary S. Collins
2024	J	`jnl`	Comparison of static and dynamic random forests models for EHR data in the presence of competing risks: predicting central line-associated bloodstream infection. CoRR Elena Albu, Shan Gao, Pieter Stijnen, Frank E. Rademakers, Christel Janssens, Veerle Cossey, Yves Debaveye, Laure Wynants, Ben Van Calster
2024	J	`jnl`	Performance evaluation of predictive AI models to support medical decisions: Overview and guidance. CoRR Ben Van Calster, Gary S. Collins, Andrew J. Vickers, Laure Wynants, Kathleen F. Kerr, Lasai Barreñada, Gaël Varoquaux, Karandeep Singh, Karel G. M. Moons, Tina Hernandez-Boussard, Dirk Timmerman, David J. Mclernon, Maarten van Smeden, Ewout W. Steyerberg
2024	J	`jnl`	Understanding random forests and overfitting: a visualization and simulation study. CoRR Lasai Barreñada, Paula Dhiman, Dirk Timmerman, Anne-Laure Boulesteix, Ben Van Calster
2024	J	`jnl`	Understanding random resampling techniques for class imbalance correction and their consequences on calibration and discrimination of clinical risk prediction models. J. Biomed. Informatics Marco Piccininni, Maximilian Wechsung, Ben Van Calster, Jessica L. Rohmann, Stefan Konigorski, Maarten van Smeden
2024	J	`jnl`	missForestPredict - Missing data imputation for prediction settings. CoRR Elena Albu, Shan Gao, Laure Wynants, Ben Van Calster
2023	J	`jnl`	Perspectives on validation of clinical predictive algorithms. npj Digit. Medicine Anne A. H. de Hond, Vaibhavi B. Shah, Ilse M. J. Kant, Ben Van Calster, Ewout W. Steyerberg, Tina Hernandez-Boussard
2023	J	`jnl`	The TRIPOD-P reporting guideline for improving the integrity and transparency of predictive analytics in healthcare through study protocols. Nat. Mac. Intell. Paula Dhiman, Rebecca Whittle, Ben Van Calster, Marzyeh Ghassemi, Xiaoxuan Liu, Melissa D. McCradden, Karel G. M. Moons, Richard D. Riley, Gary S. Collins
2023	J	`jnl`	Understanding metric-related pitfalls in image analysis validation. CoRR Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein
2022	J	`jnl`	Commentary: Artificial Intelligence and Statistics: Just the Old Wine in New Wineskins? Frontiers Digit. Health Anne De Hond, Ben Van Calster, Ewout W. Steyerberg
2022	J	`jnl`	Metrics reloaded: Pitfalls and recommendations for image analysis validation. CoRR Lena Maier-Hein, Annika Reinke, Evangelia Christodoulou, Ben Glocker, Patrick Godau, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael A. Riegler, Manuel Wiesenfarth, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Minu Dietlinde Tizabi, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, M. Jorge Cardoso, Veronika Cheplygina, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Bram van Ginneken, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Pierre Jannin, Charles E. Kahn, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Annette Kopp-Schneider, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, David Moher, Karel G. M. Moons, Henning Müller, Felix Nickel, Brennan Nichyporuk, Jens Petersen, Nasir M. Rajpoot, Nicola Rieke, Julio Saez-Rodriguez, Clarisa Sánchez Gutiérrez, Shravya Shetty, Maarten van Smeden, Carole H. Sudre, Ronald M. Summers, Abdel A. Taha, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Paul F. Jäger
2022	J	`jnl`	The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression. J. Am. Medical Informatics Assoc. Ruben van den Goorbergh, Maarten van Smeden, Dirk Timmerman, Ben Van Calster
2019	J	`jnl`	Predictive analytics in health care: how can we know it works? J. Am. Medical Informatics Assoc. Ben Van Calster, Laure Wynants, Dirk Timmerman, Ewout W. Steyerberg, Gary S. Collins
2015	J	`jnl`	A spline-based tool to assess and visualize the calibration of multiclass risk predictions. J. Biomed. Informatics K. Van Hoorde, Sabine Van Huffel, Dirk Timmerman, Tom Bourne, Ben Van Calster
2015	J	`jnl`	Improving patient prostate cancer risk assessment: Moving from static, globally-applied to dynamic, practice-specific risk calculators. J. Biomed. Informatics Andreas N. Strobl, Andrew J. Vickers, Ben Van Calster, Ewout W. Steyerberg, Robin J. Leach, Ian M. Thompson, Donna P. Ankerst
2012	J	`jnl`	It takes time: A remarkable example of delayed recognition. J. Assoc. Inf. Sci. Technol. Ben Van Calster
2009	J	`jnl`	An application of methods for the probabilistic three-class classification of pregnancies of unknown location. Artif. Intell. Medicine Ben Van Calster, George Condous, Emma Kirk, Tom Bourne, Dirk Timmerman, Sabine Van Huffel
2009	—	`ch.`	Clinical decision support for ovarian tumor diagnosis using Bayesian models: Results from the IOTA study. Computational Intelligence and Bioengineering Ben Van Calster, Olivier Gevaert, Caroline Van Holsbeke, Bart De Moor, Sabine Van Huffel, Dirk Timmerman
2008	B	`conf`	Multi-class AUC metrics and weighted alternatives. IJCNN Ben Van Calster, Vanya Van Belle, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel
2008	B	`conf`	Multi-class classification of ovarian tumors. ESANN Ben Van Calster, Dirk Timmerman, Antonia C. Testa, Lil Valentin, Sabine Van Huffel
2008	B	`conf`	Towards a Clinical Decision Support System for Pregnancies of Unknown Location. CBMS Ben Van Calster, Sabine Van Huffel, Dirk Timmerman, Emma Kirk, Tom Bourne, George Condous
2008	J	`jnl`	Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery. Neural Comput. Appl. Ben Van Calster, Dirk Timmerman, Ian T. Nabney, Lil Valentin, Antonia C. Testa, Caroline Van Holsbeke, Ignace Vergote, Sabine Van Huffel
2007	—	`conf`	Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy. ISNN (2) M. S. Hane Aung, Paulo J. G. Lisboa, Terence A. Etchells, Antonia C. Testa, Ben Van Calster, Sabine Van Huffel, Lil Valentin, Dirk Timmerman
2007	—	`conf`	Comparing Methods for Multi-class Probabilities in Medical Decision Making Using LS-SVMs and Kernel Logistic Regression. ICANN (2) Ben Van Calster, Jan Luts, Johan A. K. Suykens, George Condous, Tom Bourne, Dirk Timmerman, Sabine Van Huffel
2006	—	`conf`	Classifying ovarian tumors using Bayesian Multi-Layer Perceptrons and Automatic Relevance Determination: A multi-center study. EMBC Ben Van Calster, Dirk Timmerman, Ian T. Nabney, Lil Valentin, Caroline Van Holsbeke, Sabine Van Huffel