Benjamin Skov Kaas-Hansen
Assistant lecturer
Section of Biostatistics
Øster Farimagsgade 5 opg. B
1353 København K
ORCID: 0000-0003-1023-0371
Most downloads
-
256 downloadsPublished
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Research output: Contribution to journal › Journal article › Research › peer-review
-
82 downloadsPublished
Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records
Research output: Contribution to journal › Journal article › Research › peer-review
-
67 downloadsPublished
Different Original and Biosimilar TNF Inhibitors Similarly Reduce Joint Destruction in Rheumatoid Arthritis-A Network Meta-Analysis of 36 Randomized Controlled Trials
Research output: Contribution to journal › Review › Research › peer-review
-
42 downloadsPublished
Discrete-time survival analysis in the critically ill: a deep learning approach using heterogeneous data
Research output: Contribution to journal › Journal article › Research › peer-review
-
32 downloadsPublished
Drug interactions in hospital prescriptions in Denmark: Prevalence and associations with adverse outcomes
Research output: Contribution to journal › Journal article › Research › peer-review
ID: 185059892
Most downloads
-
256
downloads
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
82
downloads
Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
67
downloads
Different Original and Biosimilar TNF Inhibitors Similarly Reduce Joint Destruction in Rheumatoid Arthritis-A Network Meta-Analysis of 36 Randomized Controlled Trials
Research output: Contribution to journal › Review › Research › peer-review
Published