利用深度学习早期检测阿尔茨海默病

M. M. B. S. Sree
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摘要

阿尔茨海默病(AD)是一种进行性神经退行性疾病,影响着全球数百万人,并导致认知障碍。它是痴呆症最常见的病因,痴呆症是认知能力下降并影响日常生活的总称。深度学习是人工智能的一个子集,被用于阿尔茨海默病的早期检测。深度学习算法的人类水平性能已在不同学科中得到有效展示。没有一种特定的算法是万能的,但各种深度学习算法,都被用于阿尔茨海默病的早期检测。研究人员开发了一种血液检测方法,可以在症状出现之前检测出血液中促进阿尔茨海默病的化合物。这些发现可能会带来阿尔茨海默病和其他神经退行性疾病的早期诊断检测。通过对 "利用深度学习早期检测阿尔茨海默病 "的研究,我们可以更多地了解利用先进技术在疾病早期阶段识别疾病的潜力。报告还讨论了利用深度学习检测阿尔茨海默病所面临的挑战和局限性,并强调了该领域未来研究的必要性。此外,它还能让人们深入了解该疾病的进展情况,并有可能开发出更准确的诊断工具。关键词: 阿尔茨海默病 神经退行性痴呆症 早期诊断 深度学习算法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Early detection of Alzheimer’s Disease using Deep Learning
alzheimer's Disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and causes cognitive impairment. It is the most common cause of dementia, a general term for a decline in cognitive abilities that interfere with daily life. Deep Learning, the subset of Artificial Intelligence is used in the early detection of Alzheimer's Disease. The human-level performance of the Deep Learning algorithm has been effectively shown in different disciplines. There isn’t a specific algorithm that is universal, but various Deep Learning algorithms, are used for the early detection of Alzheimer’s Disease. Researchers developed a blood test that could detect Alzheimer’s Disease promoting compounds in blood before the symptoms emerged. These findings may lead to early diagnostic tests for Alzheimer’s and other neurodegenerative diseases. Through research on the “Early detection of Alzheimer’s Disease using Deep Learning”, we can learn more about the potential of using advanced technology to identify the disease at its earliest stages. It also discusses the challenges and limitations of using Deep Learning for Alzheimer's Disease detection and highlights the need for future research in this area. Additionally, it can provide insights into the progression of the disease and potentially lead to the development of more accurate diagnostic tools. KEYWORDS: Alzheimer’s Disease, neurodegenerative, dementia, Early diagnosis, Deep Learning algorithms
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