COMPANION: development of a patient-centred complexity and casemix classification for adult palliative care patients based on needs and resource use – a protocol for a cross-sectional multi-centre study
Farina Hodiamont(LMU Klinikum), Claudia Bausewein(Ludwig-Maximilians-Universität München), Reiner Leidl(Institute of Groundwater Ecology), Maximiliane Jansky(Universitätsmedizin Göttingen), Friedemann Nauck(Universitätsmedizin Göttingen), Daniela Gesell(LMU Klinikum), Caroline Schatz(Helmholtz Munich), Julia Wikert(LMU Klinikum), Steven Kranz, Anne‐Laure Boulesteix(Zimmer Biomet (Netherlands))
Cited by 32
Related Papers
Bias in random forest variable importance measures: Illustrations, sources and a solution
|BMC Bioinformatics|2007|3.7k
Conditional variable importance for random forests
|BMC Bioinformatics|2008|3.3k
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
|BMJ|2024|2.8k
Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics
|Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery|2012|937
Random forest versus logistic regression: a large-scale benchmark experiment
|BMC Bioinformatics|2018|882