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人工智能模型用于诊断和治疗病:现状和前景
Cheng Li1, Jing Liu2, Ping Fu2
1Glasgow College, University of Electronic Science and Technology of China, Chengdu, China.
Kidney diseases (Basel, Switzerland)
|July 17, 2025
概括
人工智能 (AI) 正在改变病学,提高病的诊断,预后和治疗. 本综述探讨了人工智能模型及其用于改善患者护理和数据处理的应用.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 人工智能 (AI) 正在迅速推进医疗诊断,预后和治疗在科领域.
- 人工智能集成正在彻底改变病的管理.
研究的目的:
- 提供人工智能在科应用的全面概述.
- 引入基本的人工智能模型结构,包括传统的机器学习和神经网络.
- 为了比较AI模型应用程序,提供选择建议,并讨论挑战.
主要方法:
- 关于人工智能在科应用的当前文献的综述.
- 分析传统的机器学习和神经网络模型.
- 评估AI模型的优势,局限性和用例.
主要成果:
- 人工智能在病学中的应用包括诊断,结果预测,医学图像分析,治疗建议和个性化健康管理.
- 传统的机器学习模型在各种数据集中是有效的,而神经网络在复杂和成像数据方面表现出色.
- 新兴的硬件创新有望提高临床应用的神经网络性能.
结论:
- 人工智能具有很大的潜力,可以在科中推进个性化患者护理.
- 人工智能可实现实时数据处理,导致更准确的诊断和自动化临床分析.
- 人工智能模型的战略选择和实施对于优化病管理结果至关重要.
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