机器学习和深度学习技术的概述,用于预测发作
Marco Zurdo-Tabernero1, Ángel Canal-Alonso1, Fernando de la Prieta1
1BISITE Research Group, University of Salamanca, Salamanca, Spain.
Journal of integrative bioinformatics
|December 15, 2023
概括
机器学习通过检测和预测发作,为诊断提供了一种具有成本效益的方法. 深度学习算法对于平衡预测准确性和预测中的计算需求至关重要.
科学领域:
- 神经学 神经学
- 人工智能的人工智能
背景情况:
- 是一种常见的神经系统疾病,其特点是经常性发作.
- 准确的诊断依赖于识别发作和预测未来发生的情况.
- 机器学习为快速诊断和预测发作提供了一种有希望的,具有成本效益的方法.
结论:
- 机器学习方法正在推进诊断和预测领域.
- 深度学习算法为预测发作提供了提高准确性和效率的途径.
- 未来的研究应该专注于优化预测性能和计算资源之间的平衡.
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