Piotr Jaroslaw Chmura
Research programmer
Brunak Group
Blegdamsvej 3, 2200 København N., 06 Bygning 6, Building: 06-2-21
ORCID: 0000-0002-9371-6918
Most downloads
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243 downloadsPublished
Survival prediction in intensive-care units based on aggregation of long-term disease history and acute physiology: a retrospective study of the Danish National Patient Registry and electronic patient records
Research output: Contribution to journal › Journal article › Research › peer-review
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147 downloadsPublished
The bio.tools registry of software tools and data resources for the life sciences
Research output: Contribution to journal › Letter › Research › peer-review
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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
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71 downloadsPublished
Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models: [with Author Correction]
Research output: Contribution to journal › Journal article › Research › peer-review
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66 downloadsPublished
A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories
Research output: Contribution to journal › Journal article › Research › peer-review
ID: 233701104
Most downloads
-
243
downloads
Survival prediction in intensive-care units based on aggregation of long-term disease history and acute physiology: a retrospective study of the Danish National Patient Registry and electronic patient records
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
147
downloads
The bio.tools registry of software tools and data resources for the life sciences
Research output: Contribution to journal › Letter › 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