人工智能驱动的诊断过程和综合多式模式在疼痛医学.
Marco Cascella1, Matteo L G Leoni2, Mohammed Naveed Shariff3
1Anesthesia and Pain Medicine, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84081 Baronissi, Italy.
Journal of personalized medicine
|September 28, 2024
概括
人工智能 (AI) 可以通过分析各种数据来改善疼痛诊断. 然而,道德问题和验证需求阻碍了AI在疼痛管理中的广泛临床采用.
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
- 疼痛管理 疼痛管理
背景情况:
- 由于主观性和生物心理社会因素,疼痛诊断是复杂的.
- 人工智能 (AI) 提供了增强疼痛诊断和个性化管理的潜力.
- 当前的诊断方法与疼痛表达的个体变异性作斗争.
研究的目的:
- 审查计算机辅助的疼痛诊断方法.
- 探索将AI整合到多式联络疼痛诊断模型中.
- 确定AI在疼痛管理中的挑战和未来方向.
主要方法:
- 对人工智能在疼痛诊断中的应用进行文献综述.
- 对综合面部,神经成像和生理数据的多式人工智能模型的分析.
- 讨论道德考虑和实施挑战.
主要成果:
- 人工智能显示出提高诊断准确度和治疗预测的潜力.
- 多模式人工智能模型整合了各种数据,以进行全面的疼痛评估.
- 显著的挑战包括道德问题,数据偏见和缺乏概括性.
结论:
- 人工智能对彻底改变疼痛诊断和管理具有前景.
- 解决伦理问题和确保临床验证对于人工智能采用至关重要.
- 为了在不同的医疗保健环境中实施AI,需要标准化的协议.
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