用深度学习来诊断痴呆症的语音和语言处理:系统性审查
Mengke Shi1, Gary Cheung2, Seyed Reza Shahamiri1
1Department of Electrical, Computer and Software Engineering, Faculty of Engineering, University of Auckland, Private Bag 92019, Building 405, Level 6, Room 669, 3 Garfton Road, Auckland 1142, New Zealand.
Psychiatry research
|October 21, 2023
概括
深度学习 (DL) 技术在使用语音和语言数据诊断痴呆症方面表现有前途. 这些人工智能工具有效地区分健康人和痴呆症患者,有助于早期检测.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 计算语言学 计算语言学
背景情况:
- 痴呆症诊断是复杂的,资源密集的,并面临着可访问性问题,特别是在低收入和中等收入国家.
- 早期痴呆症诊断使干预措施能够减缓疾病的进展,并减少患者和社会负担.
- 语音和语言数据为开发新型诊断工具提供了可访问的资源.
结论:
- 基于深度学习的语音和语言技术显示出有很大的潜力来帮助痴呆症诊断过程.
- 人工智能的进步为可访问和及时检测痴呆症提供了新的可能性.
- 需要进一步的研究来解决现有的挑战,并优化DL应用程序痴呆症诊断.
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