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Design of Interpretable end-to-end Deep Learning Models for Diagnosis of Sleep Disorders and Sleep Health Evaluationion
Brink-Kjær, Andreas
(PhD Student)
Karstoft, Henrik
(Examiner)
Sørensen, Helge Bjarup Dissing
(Main Supervisor)
Mignot, Emmanuel
(Supervisor)
Jennum, Poul Jørgen
(Supervisor)
Digital Health
Department of Health Technology
Overview
Fingerprint
Research output
(1)
Project Details
Status
Finished
Effective start/end date
01/03/2019
→
03/08/2022
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Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Sleep Quality
Medicine and Dentistry
100%
Sleep Disorder
Medicine and Dentistry
100%
Parasomnia
Medicine and Dentistry
100%
Rapid Eye Movement Sleep
Neuroscience
100%
Behavior Disorder
Neuroscience
100%
REM Sleep
Biochemistry, Genetics and Molecular Biology
100%
Cognition
Biochemistry, Genetics and Molecular Biology
100%
Clinician
Medicine and Dentistry
40%
Research output
Research output per year
2022
2022
2022
1
Ph.D. thesis
Research output per year
Research output per year
Design of Interpretable End-to-End Deep Learning Models for Diagnosis of Sleep Disorders and Sleep Quality Evaluation
Brink-Kjær, A.
,
2022
,
DTU Health Technology
.
326 p.
Research output
:
Book/Report
›
Ph.D. thesis
Sleep Disorder
100%
Sleep Quality
100%
Parasomnia
100%
Behavior Disorder
100%
Rapid Eye Movement Sleep
100%