用于诊断膀病理生理学的人工智能:一个更新的审查和未来的前景
1Institut Hospitalo-Universitaire, University of Bordeaux, Pessac 33600, France.
Bladder (San Francisco, Calif.)
|August 1, 2025
概括
人工智能 (AI) 在诊断膀病理生理学方面表现有前途,包括膀癌和神经性膀等疾病. 数据质量和临床整合的进一步进步是实现AI在膀疾病诊断中的全部潜力的关键.
科学领域:
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 膀病理生理学包括各种疾病,如癌症,感染和神经性膀.
- 这些疾病的诊断和治疗具有独特的挑战.
- 人工智能 (AI) 有潜力彻底改变膀疾病的诊断方法.
研究的目的:
- 审查AI在诊断膀病理生理学的整合.
- 突出人工智能技术 (机器学习,深度学习) 和它们的应用.
- 评估当前的人工智能工具,它们的准确性,临床实用性和挑战.
主要方法:
- 关于人工智能在膀病理生理学诊断中的应用的综合文献综述.
- 分析机器学习和深度学习技术.
- 评估人工智能诊断工具,数据质量,可解释性和临床整合.
主要成果:
- 人工智能,特别是机器学习和深度学习,在识别和分类膀疾病方面显示出巨大的潜力.
- 当前的人工智能工具显示出不同程度的准确性和临床实用性.
- 挑战包括数据质量,算法解释性和工作流集成.
结论:
- 人工智能对提高膀病理生理学诊断具有相当大的希望.
- 在数据质量,可解释性和临床整合方面取得持续进展至关重要.
- 未来的人工智能创新旨在实现更准确,更有效和更个性化的患者护理.
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