The most frequent kind of dementia of the nervous system, Alzheimer's disease, weakens several brain processes (such as memory) and eventually results in death. The clinical study uses magnetic resonance imaging to diagnose AD. Deep learning algorithms are capable of pattern recognition and feature extraction from the inputted raw data. As early diagnosis and stage detection are the most crucial elements in enhancing patient care and treatment outcomes, deep learning algorithms for MRI images have recently allowed for diagnosing a medical condition at the beginning stage and identifying particular symptoms of Alzheimer's disease. As a result, we aimed to analyze five specific studies focused on AD diagnosis using MRI-based deep learning algorithms between 2021 and 2023 in this study. To completely illustrate the differences between these techniques and comprehend how deep learning algorithms function, we attempted to explore selected approaches in depth.

翻译：阿尔茨海默病是最常见的神经系统痴呆类型，会削弱多种大脑功能（如记忆），并最终导致死亡。临床研究利用磁共振成像诊断阿尔茨海默病。深度学习算法能够从输入的原始数据中识别模式并提取特征。由于早期诊断和分期检测是改善患者护理和治疗效果的最关键因素，基于MRI图像的深度学习算法近年来已使疾病早期阶段的诊断成为可能，并能识别阿尔茨海默病的特定症状。因此，本研究旨在分析2021至2023年间五项专注于基于MRI深度学习算法诊断阿尔茨海默病的特定研究。为全面阐明这些技术之间的差异并理解深度学习算法的工作原理，我们试图深入探讨选定的方法。