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Epidemiology and evaluation of breathlessness - A data-driven approach

Olsson, Max LU orcid (2024) In Lund University, Faculty of Medicine Doctoral Dissertation Series
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Jenkins, Christine, Respiratory Group, The George Institute for Global Health, Sydney, Australia
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Andfåddhet, maskininlärning, epidmiologi, machine learning, Breathlessnes, Dyspnoea, Dyspné
in
Lund University, Faculty of Medicine Doctoral Dissertation Series
issue
2024:101
pages
80 pages
publisher
Lund University, Faculty of Medicine
defense location
Stora Algatan Hörsal, Stora Algatan 4, Lund
defense date
2024-09-13 13:00:00
ISSN
1652-8220
ISBN
978-91-8021-597-8
language
English
LU publication?
yes
id
e3b2924b-ab07-4940-a4cf-6025dfe738ef
date added to LUP
2024-08-22 10:24:06
date last changed
2025-04-04 14:00:36
@phdthesis{e3b2924b-ab07-4940-a4cf-6025dfe738ef,
  author       = {{Olsson, Max}},
  isbn         = {{978-91-8021-597-8}},
  issn         = {{1652-8220}},
  keywords     = {{Andfåddhet; maskininlärning; epidmiologi; machine learning; Breathlessnes; Dyspnoea; Dyspné}},
  language     = {{eng}},
  number       = {{2024:101}},
  publisher    = {{Lund University, Faculty of Medicine}},
  school       = {{Lund University}},
  series       = {{Lund University, Faculty of Medicine Doctoral Dissertation Series}},
  title        = {{Epidemiology and evaluation of breathlessness - A data-driven approach}},
  url          = {{https://lup.lub.lu.se/search/files/193747847/Max_Olsson_LUCRIS_thesis.pdf}},
  year         = {{2024}},
}