GPT-3 Alzheimer
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健康和医疗卫生保健

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AI Model GPT-3可能预测痴呆症和阿尔茨海默氏病

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Chatgpt背后的AI可以帮助发现阿尔茨海默氏病的早期迹象。 Drexel University的生物医学工程学院的研究最近表明,OpenAI的GPT-3计划可以从自发性演讲中确定线索,这些线索在预测痴呆症的早期阶段中精确80%。

阿尔茨海默氏病是目前无法治愈的脑部疾病。言语是一种典型的人类能力,已成为AD等神经退行性疾病的重要生物标志物。 AI驱动的语音分析可以帮助识别AD吗?我们在这项研究中表明,由OpenAI产生的特定语言模型GPT-3可能是通过语音对AD进行早期预测的一步。具体而言,我们证明,由GPT-3提供支持的文本嵌入可以可靠地用于(1)将AD的个体与健康对照区分开,并且(2)仅基于语音数据推断受试者的认知测试评分。我们进一步表明,嵌入的文本大大优于常规功能的方法,甚至在主流使用微型模型的主流使用方面具有竞争力。我们的结果表明,开发和翻译完全可部署的AI驱动的工具具有巨大的潜力,可早期诊断痴呆症和直接量身定制的干预措施,从而改善痴呆症患者的生活质量。

资料来源:https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000168

原文:

AI Behind ChatGPT Could Help Spot Early Signs of Alzheimer's Disease. Research from Drexel University’s School of Biomedical Engineering, Science and Health Systems recently demonstrated that OpenAI’s GPT-3 program can identify clues from spontaneous speech that are 80% accurate in predicting the early stages of dementia.

Alzheimer’s disease is a currently incurable brain disorder. Speech, a quintessentially human ability, has emerged as an important biomarker of neurodegenerative disorders like AD. Can AI-driven speech analysis help identify AD? We show in this study that GPT-3, a specific language model produced by OpenAI, could be a step towards early prediction of AD through speech. Specifically, we demonstrate that text embedding, powered by GPT-3, can be reliably used to (1) distinguish individuals with AD from healthy controls, and (2) infer the subject’s cognitive testing score, both solely based on speech data. We further show that text embedding considerably outperforms the conventional feature-based approach and even performs competitively with the mainstream use of fine-tuned models. Our results suggest that there is a huge potential to develop and translate a fully deployable AI-driven tools for early diagnosis of dementia and direct tailored interventions to individual needs, thereby improving quality of life for individuals with dementia.

Source: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000168

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