关于阿尔茨海默病的某些研究:全面回顾

Arunachalam V, Chitra S, Lakshmi K
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引用次数: 0

摘要

大脑是人体的中枢控制中心,随着时代的进步,越来越多的新脑部疾病被发现。脑部疾病是指任何干扰大脑正常功能的医学问题或紊乱。本综述简要介绍了针对神经系统疾病的各类深度学习模型,以及帕金森症和阿尔茨海默氏症等神经退行性疾病。除了综述研究中常用的作为脑部疾病数据主要来源的各种数据集标识符外,还研究了其他 40 种方法。此外,还讨论并记录了 AUC、灵敏度、特异性、准确性和其他性能评估参数。本文简要总结了综述文章中的主要发现,并讨论了有关基于机器学习和深度学习的脑疾病诊断方法的几个主要问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Certain Studies on Alzheimer's disease: A Comprehensive Review
The brain serves as the central control centre for our body, and as time progresses, an increasing number of new brain diseases are being identified. A brain disease is any medical problem or disorder that interferes with the brain's normal functioning. This review briefs about various types of deep learning models for neurological disorders, in addition to neurodegenerative conditions like Parkinson's and Alzheimer's. In addition to various dataset identifiers commonly used as the primary source of brain disease data in the reviewed studies, forty other methodologies are examined. AUC, sensitivity, specificity, accuracy, and other performance evaluation parameters have also been addressed and recorded. The key findings from the reviewed articles are briefly summarized, and several major issues regarding machine learning and deep learning-based diagnostic approaches for brain diseases are discussed.
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