Enhancing Early Detection of Obstructive Sleep Apnea Syndrome: Integrative Application of Artificial Intelligence Technologies

Zaga F.R. · Gaceta Medica Boliviana (2024) · DOI: 10.47993/gmb.v47i2.691

Resumen

Obstructive sleep apnea syndrome (OSAS) poses serious health risks, which is why its early detection is crucial for effective treatment. Objective: This work aims to analyze the potential of artificial intelligence (AI) in the detection of OSAS, specifically using polysomnography data. Method: For this purpose, a bibliographic review was carried out through an exhaustive search of the scientific literature related to OSAS and its diagnosis. Results: According to the studies analyzed, AI models accurately predict the risk of OSA. Machine learning methods show promise in reviewing snoring sounds and facial images for OSA diagnosis. Conclusion: AI-based technology improves the OSAS detection process through non-invasive and efficient methods. Incorporating AI into multiple diagnostic approaches provides a comprehensive strategy for early diagnosis of OSAS. However, further validation in various populations is still necessary.

Instituciones: Universidad Privada del Norte