We know that in the absence of treatment, sleep apnea can have a devastating effect on a patient’s well-being.
Polysomnography is the current gold standard for diagnosing obstructive sleep apnea, but it is time-consuming, expensive, and difficult to get. There are also difficulties in the primary care setting in identifying obstructive sleep apnea. Patients will benefit from a novel diagnostic technique that tackles the constraints of polysomnography and streamlines the diagnosis process thanks to artificial intelligence technology.
An investigation into the barriers to the use of artificial intelligence systems in obstructive sleep apnea diagnostics is the goal of a recent research project for the Journal of Otolaryngology – Head & Neck Surgery at Memorial University.
A thorough understanding of these issues is necessary for effective implementation of this new technology as quickly as possible. To better understand how artificial intelligence can be used in diagnosing obstructive sleep apnea as well as what obstacles it faces, a comprehensive literature analysis was conducted.
Technology, data, regulation, human resources, education, and culture were some of the categories in which the hurdles were categorized. Artificial intelligence implementation in medical diagnostics faces many of the same issues. Research in the future will focus on finding answers to the issues raised in this study.