@article{ETD,
      school = {M.S.},
      author = {Li, Jason},
      url = {http://digitalcollections.ohsu.edu/record/7677},
      title = {Finding subtypes of obstructive sleep apnea using cluster  analysis},
      publisher = {Marylhurst University: Oregon Health and Science  University},
      abstract = {One hundred million people worldwide have obstructive  sleep apnea (OSA), a disorder characterized by collapse of  the upper airway and repeated pauses in breathing  throughout sleep(1-5). Sleep fragmentation caused by sleep  apnea can lead to daytime sleepiness(2, 4, 6, 7), increased  risk for motor accidents(2, 6), and reduced quality of  life. The physiological changes associated with these  pauses are believed to contribute to the development of  hypertension(2-4), diabetes mellitus(2), obesity(2),  stroke(2, 3), and heart disease(2, 3).},
      number = {ETD},
      doi = {https://doi.org/10.6083/m4wh2pht},
      recid = {7677},
      address = {2017},
}