Barriers of artificial intelligence implementation in the diagnosis of obstructive sleep apnea.

Journal: Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
Published Date:

Abstract

BACKGROUND: Obstructive sleep apnea is a common clinical condition and has a significant impact on the health of patients if untreated. The current diagnostic gold standard for obstructive sleep apnea is polysomnography, which is labor intensive, requires specialists to utilize, expensive, and has accessibility challenges. There are also challenges with awareness and identification of obstructive sleep apnea in the primary care setting. Artificial intelligence systems offer the opportunity for a new diagnostic approach that addresses the limitations of polysomnography and ultimately benefits patients by streamlining the diagnostic expedition.

Authors

  • Hannah L Brennan
    Faculty of Medicine, Memorial University of Newfoundland and Labrador, 98 Pearltown Rd, St. John's, NL, A1G 1P3, Canada. hlb423@mun.ca.
  • Simon D Kirby
    Faculty of Medicine, Memorial University of Newfoundland and Labrador, 98 Pearltown Rd, St. John's, NL, A1G 1P3, Canada.