人工智能模型在尾炎管理中的系统整合:全面审查
Ivan Maleš1, Marko Kumrić2,3, Andrea Huić Maleš4
1Department of Abdominal Surgery, University Hospital of Split, Spinčićeva 1, 21000 Split, Croatia.
Diagnostics (Basel, Switzerland)
|April 12, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在彻底改变急性尾炎护理,改善诊断,治疗和从分拣到术后管理的患者结果. 这篇评论强调了人工智能.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 手术创新 在外科创新.
背景情况:
- 急性尾炎的治疗依赖于及时诊断和有效治疗.
- 当前的诊断和治疗途径在准确性和效率方面面临挑战.
- 人工智能 (AI) 和机器学习 (ML) 的整合提供了潜在的解决方案.
研究的目的:
- 在急性尾炎护理的整个领域全面审查AI和ML应用.
- 评估人工智能对诊断准确度,治疗优化和患者治疗结果的影响.
- 确定人工智能在尾炎管理中的当前挑战和未来方向.
主要方法:
- 在主要的科学数据库 (PubMed/MEDLINE,IEEE Xplore,arXiv,Web of Science,Scopus) 进行系统的文献搜索,截至2025年2月14日.
- 在尾炎的分拣,诊断,严重程度预测,手术内辅助和术后管理中对AI/ML应用的审查.
- 对评估AI模型性能,临床实用性和整合挑战的研究进行分析.
主要成果:
- 人工智能展示了快速选和使用各种数据准确诊断尾炎的潜力.
- 机器学习算法可以提高诊断准确度,预测疾病严重程度,并指导治疗决策.
- 新兴的人工智能工具有助于手术内手术并预测术后并发症,如和败血症.
- 放射学通过先进的成像数据分析提高了诊断精度.
结论:
- 人工智能和机器学习正在改变急性尾炎护理,提供增强的诊断能力和个性化治疗策略.
- 尽管潜力很大,但数据质量,可解释性,伦理和临床整合方面的挑战仍需要解决.
- 未来的研究应该专注于开发综合的人工智能辅助工作流程,以优化患者的治疗结果,并确保公平的获取.
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