The role of artificial intelligence in the treatment of obstructive sleep apnea.

BACKGROUND: The first-line and most common treatment for obstructive sleep apnea is nasal continuous positive airway pressure, which serves as a pneumatic splint to stabilize the upper airway and is effective when used with appropriate adherence. Continuous positive airway pressure compliance rates remain significantly low despite machine improvements and compliance intervention. Other treatment options include oral appliances, myofunctional therapy, and surgery. The aim of this project is to elucidate the role of artificial intelligence within improving the treatment of obstructive sleep apnea. METHODS: Related publications between 1999 and 2022 were reviewed from PubMed and Embase databases utilizing search terms "artificial intelligence," "machine learning," "obstructive sleep apnea," and "treatment." Both authors independently screened the results by title/abstract then by full text review. 126 non-duplicate articles were screened, 38 articles were included after title and abstract screen and 30 articles were included after full text review. The inclusion criteria are outline in the PICO framework and involved studies focused on artificial intelligence application in guiding and evaluating obstructive sleep apnea treatment. Non-English articles were excluded. RESULTS: The role of artificial intelligence in the treatment of OSA was categorized into the following sections: Predicting treatment outcomes of various treatment options, Improving/Evaluating treatment, and Personalizing treatment with improving understanding of underlying mechanisms of OSA. CONCLUSIONS: Artificial intelligence has the capacity to improve the treatment of OSA through predicting outcomes of treatment options, evaluating the treatment the patient is currently utilizing and increasing understanding of the mechanisms that contribute to OSA disease process and physiology. Implementing AI in guiding treatment decisions allows patients to connect with treatment methods that would be most effective on an individual basis.

Intraoperative video recording in otolaryngology for surgical education: evolution and considerations.

BACKGROUND: Otolaryngology is a surgical speciality well suited for the application of intraoperative video recording as an educational tool considering the number procedures within the speciality that utilize digital technology. Intraoperative recording has been utilized in endoscopic surgeries and in evaluating technique in mastoidectomy, myringotomy and grommet insertion. The impact of intra-operative video recording in otolaryngology education is vast in creating access to surgical videos for preparation outside the operating room to individualized coaching and assessment. The purpose of this project is to highlight the role of intraoperative video recording in otolaryngology training and elucidate the challenges and considerations associated with implementation. METHODS: Related publications between 1999 to 2022 were reviewed from PubMed and Embase databases utilizing search terms "intraoperative videography," "video recording surgery," "otolaryngology," and "surgical education." 109 articles were screened independently by HB and SK, by title and abstract then full text review. 28 articles from the original search and 6 from the secondary reference review were included. RESULTS: The application of intraoperative video recording is evident in otolaryngology surgeries including endoscopic sinus surgery, laryngeal surgery, and other endoscopic procedures. There have been significant advancements in recording tools, including devices that can capture the surgeon's perspective. The considerations and challenges identified with utilizing this educational tool were categorized into different themes including ethics/consent, regulation, liability, data, technology, and human resources. CONCLUSION: Intra-operative video recording has been demonstrated to have significant impact within otolaryngology education. It is critical to elucidate the challenges and considerations involved to utilize this educational tool effectively. Future directives will see video-based performance analytics providing comparative metrics to encourage precise coaching of surgical residents.

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

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. MAIN BODY: The purpose of this project is to elucidate the barriers that exist in the implementation of artificial intelligence systems into the diagnostic context of obstructive sleep apnea. It is essential to understand these challenges in order to proactively create solutions and establish an efficient adoption of this new technology. The literature regarding the evolution of the diagnosis of obstructive sleep apnea, the role of artificial intelligence in the diagnosis, and the barriers in artificial intelligence implementation was reviewed and analyzed. CONCLUSION: The barriers identified were categorized into different themes including technology, data, regulation, human resources, education, and culture. Many of these challenges are ubiquitous across artificial intelligence implementation in any medical diagnostic setting. Future research directions include developing solutions to the barriers presented in this project.