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Overcoming Alzheimer’s Disease Stigma by Leveraging Artificial Intelligence and Blockchain Technologies

机译:利用人工智能和区块链技术克服阿尔茨海默氏病的耻辱

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摘要

Alzheimer’s disease (AD) imposes a considerable burden on those diagnosed. Faced with a neurodegenerative decline for which there is no effective cure or prevention method, sufferers of the disease are subject to judgement, both self-imposed and otherwise, that can have a great deal of effect on their lives. The burden of this stigma is more than just psychological, as reluctance to face an AD diagnosis can lead people to avoid early diagnosis, treatment, and research opportunities that may be beneficial to them, and that may help progress towards fighting AD and its progression. In this review, we discuss how recent advents in information technology may be employed to help fight this stigma. Using artificial intelligence (AI) technologies, specifically natural language processing (NLP), to classify the sentiment and tone of texts, such as those of online posts on various social media sites, has proven to be an effective tool for assessing the opinions of the general public on certain topics. These tools can be used to analyze the public stigma surrounding AD. Additionally, there is much concern among individuals that an AD diagnosis, or evidence of pre-clinical AD such as a biomarker or imaging test results, may wind up unintentionally disclosed to an entity that may discriminate against them. The lackluster security record of many medical institutions justifies this fear to an extent. Adopting more secure and decentralized methods of data transfer and storage, and giving patients enhanced ability to control their own data, such as a blockchain-based method, may help to alleviate some of these fears.
机译:阿尔茨海默氏病(AD)给诊断出的人带来了相当大的负担。面对没有有效治愈或预防方法的神经退行性衰退,该疾病的患者必须接受自我判断或其他判断,这可能对其生活产生很大影响。这种耻辱的负担不仅仅是心理上的负担,因为不愿面对AD诊断会导致人们避免可能对他们有利的早期诊断,治疗和研究机会,并可能有助于对抗AD及其进展。在这篇评论中,我们讨论了如何利用最新的信息技术来帮助消除这种污名。事实证明,使用人工智能(AI)技术(尤其是自然语言处理(NLP))对文本的情感和语气进行分类,例如各种社交媒体网站上的在线帖子的情感和语调,是评估用户意见的有效工具。公众就某些主题。这些工具可用于分析围绕AD的公众污名。此外,个人之间非常担心,AD诊断或临床前AD的证据(例如生物标志物或影像学检查结果)可能无意间公开给可能歧视他们的实体。许多医疗机构的安全记录不佳在一定程度上证明了这种担心。采用更安全和分散的数据传输和存储方法,并为患者提供增强的控制自己的数据的能力,例如基于区块链的方法,可能有助于减轻这些担忧。

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