在智能医疗保健中基于机器学习和深度学习的方法:最近的进展,应用,挑战和机会
Anichur Rahman1,2, Tanoy Debnath2,3, Dipanjali Kundu1
1Department of CSE, National Institute of Textile Engineering and Research (NITER), Constituent Institute of the University of Dhaka, Savar, Dhaka-1350.
AIMS public health
|April 15, 2024
概括
机器学习 (ML) 和深度学习 (DL) 在医疗保健领域具有重大潜力. 本调查详细介绍了智能医疗保健系统的应用,好处和未来方向.
科学领域:
- 人工智能在医学中的应用
- 计算健康信息学 计算健康信息学
背景情况:
- 机器学习 (ML) 和深度学习 (DL) 在现代智能医疗保健中是至关重要的.
- 这些技术解决了疾病预测,药物发现和医学成像方面的挑战.
研究的目的:
- 为医疗保健系统提供ML和DL的全面调查.
- 突出最先进的功能,整合的好处,应用程序和未来的指导方针.
主要方法:
- 通过使用著名期刊和会议数据库进行文献综述.
- 识别和分析学术作品,使用与医疗保健中的ML和DL相关的特定关键词.
主要成果:
- 总结了智能医疗保健基于ML-DL分析的当前进展.
- 详细介绍了ML医疗保健,DL医疗保健和ML-DL医疗保健服务的整合.
- 在医疗保健行业提出了各种ML和DL应用.
结论:
- 确定了关键的研究挑战,并为未来的研究提供了建议.
- 强调了ML和DL在推进医疗保健方面的变革潜力.
- 强调需要在这个跨学科领域继续进行研究和开发.
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