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彻底改变痴呆症检测:利用视力和Swin变压器进行早期诊断

Rini P L¹, Gayathri K S¹

¹Department of Information Technology, Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, India.

American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics

|April 15, 2024

概括

早期发现痴呆症对于管理至关重要. 先进的AI算法,如Swin变压器,在识别微妙的大脑变化以及时诊断和干预方面表现出有希望.

科学领域:

神经学神经学
人工智能的人工智能
医疗成像医学成像

背景情况:

痴呆症是一个日益严重的全球健康问题,预计到2050年,该病例将增加三倍.
与痴呆症相关的认知衰退显著影响日常功能和决策.
早期发现对于有效的管理和干预策略至关重要.

研究的目的:

探索先进人工智能的潜力,特别是计算机视觉和深度学习,用于早期发现痴呆症.
评估不同AI算法的有效性,从脑成像数据中识别痴呆症的早期症状.

主要方法:

利用计算机视觉和深度学习算法来分析医学成像数据,例如正子发射断层扫描 (PET) 扫描.
对比了Swin变压器,视觉变压器和卷积神经网络算法的性能,用于检测暗示痴呆症的微妙大脑变化.

主要成果:

与其他测试的算法相比,Swin变压器算法在检测痴呆症方面表现出更高的整体准确性.
人工智能对成像数据的分析成功地发现了微妙的结构性大脑变化,促进了早期诊断.

结论:

早期发现痴呆症对于主动管理,个性化护理和实施预防措施至关重要.
人工智能技术,特别是Swin变压器,为提高痴呆症诊断的准确性和及时性提供了一个有希望的途径.
人工智能的进步可以显著提高患者的治疗结果,并减少与痴呆症相关的医疗负担.

关键词:

在美国,CNN是CNN.皮特扫描是PET扫描.斯温变压器是什么意思深度学习是一种深度学习.痴呆症痴呆症是一种痴呆症.视觉变压器视觉变压器

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