Center for Information and Communications Technology Research (CITIC), Universidade da Coruña, 15071 A Coruña, Spain.
Sleep Med Clin. 2023 Sep;18(3):277-292. doi: 10.1016/j.jsmc.2023.05.002. Epub 2023 Jun 15.
Automatic polysomnography analysis can be leveraged to shorten scoring times, reduce associated costs, and ultimately improve the overall diagnosis of sleep disorders. Multiple and diverse strategies have been attempted for implementation of this technology at scale in the routine workflow of sleep centers. The field, however, is complex and presents unsolved challenges in a number of areas. Recent developments in computer science and artificial intelligence are nevertheless closing the gap. Technological advances are also opening new pathways for expanding our current understanding of the domain and its analysis.
自动多导睡眠图分析可以缩短评分时间，降低相关成本，并最终改善睡眠障碍的整体诊断。为了在睡眠中心的常规工作流程中大规模实施这项技术，已经尝试了多种不同的策略。然而，该领域非常复杂，在许多方面都存在尚未解决的挑战。计算机科学和人工智能的最新发展正在缩小这一差距。技术进步也为我们扩大对该领域及其分析的现有理解开辟了新的途径。
