Petsiou Dioni-Pinelopi, Martinos Anastasios, Spinos Dimitrios
Otolaryngology-Head and Neck Surgery, National and Kapodistrian University of Athens, School of Medicine, Athens, GRC.
Otolaryngology-Head and Neck Surgery, Gloucestershire Hospitals NHS Foundation Trust, Gloucester, GBR.
Cureus. 2023 Sep 2;15(9):e44591. doi: 10.7759/cureus.44591. eCollection 2023 Sep.
The applications of artificial intelligence (AI) in temporal bone (TB) imaging have gained significant attention in recent years, revolutionizing the field of otolaryngology and radiology. Accurate interpretation of imaging features of TB conditions plays a crucial role in diagnosing and treating a range of ear-related pathologies, including middle and inner ear diseases, otosclerosis, and vestibular schwannomas. According to multiple clinical studies published in the literature, AI-powered algorithms have demonstrated exceptional proficiency in interpreting imaging findings, not only saving time for physicians but also enhancing diagnostic accuracy by reducing human error. Although several challenges remain in routinely relying on AI applications, the collaboration between AI and healthcare professionals holds the key to better patient outcomes and significantly improved patient care. This overview delivers a comprehensive update on the advances of AI in the field of TB imaging, summarizes recent evidence provided by clinical studies, and discusses future insights and challenges in the widespread integration of AI in clinical practice.
近年来，人工智能（AI）在颞骨（TB）成像中的应用备受关注，给耳鼻咽喉科和放射学领域带来了变革。准确解读TB疾病的成像特征在诊断和治疗一系列耳部相关疾病中起着至关重要的作用，这些疾病包括中耳和内耳疾病、耳硬化症以及前庭神经鞘瘤。根据文献中发表的多项临床研究，人工智能驱动的算法在解读成像结果方面表现出卓越的能力，不仅为医生节省了时间，还通过减少人为错误提高了诊断准确性。尽管在常规依赖人工智能应用方面仍存在一些挑战，但人工智能与医疗保健专业人员之间的合作是实现更好的患者预后和显著改善患者护理的关键。本综述全面更新了人工智能在TB成像领域的进展，总结了临床研究提供的最新证据，并讨论了人工智能在临床实践中广泛整合的未来前景和挑战。
