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Riccardo De Bin
Riccardo De Bin
Associate Professor, Department of Mathematics, University of Oslo
Bestätigte E-Mail-Adresse bei math.uio.no - Startseite
Titel
Zitiert von
Zitiert von
Jahr
IPF-LASSO: integrative-penalized regression with penalty factors for prediction based on multi-omics data
AL Boulesteix, R De Bin, X Jiang, M Fuchs
Computational and mathematical methods in medicine 2017, 2017
782017
Subsampling versus bootstrapping in resampling‐based model selection for multivariable regression
R De Bin, S Janitza, W Sauerbrei, AL Boulesteix
Biometrics 72 (1), 272-280, 2016
702016
Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex
P Friederich, G dos Passos Gomes, R De Bin, A Aspuru-Guzik, D Balcells
Chemical science 11 (18), 4584-4601, 2020
692020
Investigating the prediction ability of survival models based on both clinical and omics data: two case studies
R De Bin, W Sauerbrei, AL Boulesteix
Statistics in Medicine 33 (30), 5310 - 5329, 2014
512014
Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages CoxBoost and mboost
R De Bin
Computational Statistics 31 (2), 513-531, 2016
382016
Accuracy of four imaging techniques for diagnosis of posterior pelvic floor disorders
IMA van Gruting, A Stankiewicz, K Kluivers, R De Bin, H Blake, AH Sultan, ...
Obstetrics & Gynecology 130 (5), 1017-1024, 2017
302017
A novel approach to the clustering of microarray data via nonparametric density estimation
R De Bin, D Risso
BMC bioinformatics 12 (1), 1-8, 2011
302011
On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models
RDB H Seibold, C Bernau, AL Boulesteix
Computational Statistics 33 (3), 1195–1215, 2018
23*2018
Integrated likelihoods in models with stratum nuisance parameters
R De Bin, N Sartori, TA Severini
Electronic Journal of Statistics 9, 1474-1491, 2015
20*2015
On the asymptotic behaviour of the variance estimator of a U-statistic
M Fuchs, R Hornung, AL Boulesteix, R De Bin
Journal of Statistical Planning and Inference 209, 101-111, 2020
17*2020
Predicting time to graduation at a large enrollment American university
JM Aiken, R De Bin, M Hjorth-Jensen, MD Caballero
Plos one 15 (11), e0242334, 2020
152020
Added predictive value of omics data: specific issues related to validation illustrated by two case studies
R De Bin, T Herold, AL Boulesteix
BMC Medical Research Methodology 14, 117, 2014
142014
Selection of variables for multivariable models: Opportunities and limitations in quantifying model stability by resampling
C Wallisch, D Dunkler, G Rauch, R De Bin, G Heinze
Statistics in medicine 40 (2), 369-381, 2021
122021
A plea for taking all available clinical information into account when assessing the predictive value of omics data
A Volkmann, R De Bin, W Sauerbrei, AL Boulesteix
BMC medical research methodology 19 (1), 1-15, 2019
122019
Multivariable Fractional Polynomials for lithium-ion batteries degradation models under dynamic conditions
C Bertinelli Salucci, A Bakdi, IK Glad, E Vanem, R De Bin
Journal of Energy Storage 52 (Part B), 2022
9*2022
Framework for evaluating statistical models in physics education research
JM Aiken, R De Bin, HJ Lewandowski, MD Caballero
Physical Review Physics Education Research 17 (2), 020104, 2021
92021
Accounting for grouped predictor variables or pathways in high-dimensional penalized Cox regression models
S Belhechmi, RD Bin, F Rotolo, S Michiels
BMC bioinformatics 21 (1), 1-20, 2020
82020
Combining clinical and molecular data in regression prediction models: insights from a simulation study
R De Bin, AL Boulesteix, A Benner, N Becker, W Sauerbrei
Briefings in Bioinformatics 21 (6), 1904-1919, 2020
82020
Does 4D transperineal ultrasound have additional value over 2D transperineal ultrasound for diagnosing posterior pelvic floor disorders in women with obstructed defecation …
IMA van Gruting, K Kluivers, AH Sultan, R De Bin, A Stankiewicz, H Blake, ...
Ultrasound in Obstetrics & Gynecology 52 (6), 784-791, 2018
72018
A decision support system for safer airplane landings: Predicting runway conditions using XGBoost and explainable AI
AD Midtfjord, R De Bin, AB Huseby
Cold Regions Science and Technology 199, 103556, 2022
4*2022
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