人工智能优化了慢性鼻炎的标准化诊断和治疗
Yang-Yang Liu1, Shao-Peng Jiang1, Ying-Bin Wang1
1Department of Otolaryngology, First Affiliated Hospital of Gannan Medical University, Ganzhou, China.
Frontiers in physiology
|April 4, 2025
概括
人工智能 (AI) 为慢性鼻炎 (CRS) 的诊断和治疗提供了有希望的解决方案,提高了准确性和效率. 然而,数据标准化和人工智能解释性等挑战需要解决,以实现广泛的临床采用.
科学领域:
- 医疗信息学 医疗信息学
- 耳鼻喉科 耳鼻喉科 耳鼻喉科
- 人工智能的人工智能
背景情况:
- 慢性鼻炎 (CRS) 的标准化管理需要准确的诊断,个性化治疗和有效的治疗后护理.
- 人工智能 (AI) 越来越多地集成到医疗应用中,为CRS提供新的解决方案.
- 人工智能辅助系统正在出现,用于诊断和治疗CRS,影响临床实践.
研究的目的:
- 总结关于人工智能辅助系统在CRS临床诊断和治疗中的研究进展.
- 专注于AI在成像,病理诊断,预后预测和CRS治疗优化方面的作用.
- 概述人工智能在标准化CRS诊断和治疗方面的进展和挑战.
主要方法:
- 在PubMed,Web of Science和互联网搜索引擎上使用关键字进行文献搜索:"人工智能"",机器学习"和"慢性鼻炎".
- 包括在过去7年内发表的研究,重点关注CRS诊断,治疗和预后中的AI应用.
- 文献根据其在CRS管理中的临床应用进行了分类.
主要成果:
- 在CRS成像和病理诊断中的AI应用可以减少周转时间和诊断成本.
- 人工智能在个性化医疗和对CRS患者准确的预后预测方面展示了潜力.
- 关键的挑战包括缺乏人工智能产品标准,数据标准化,供应商之间的协作,人工智能可解释性和数据隐私问题.
结论:
- 人工智能具有显著的潜力,可以优化CRS的诊断和治疗.
- 需要进一步的研究和改进,以克服当前的挑战,并实现AI在CRS管理中的全部潜力.
- 提供了利用人工智能的建议,以推动CRS诊断和治疗的标准化.
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