Piloting A Secure, Scalable, Infrastructure for AI Dementia Research On Routinely Collected Data

痴呆症影响着全球5500万人，到2050年将超过1.35亿人。这场与年龄相关的全球大流行是人工智能的理想应用，可以影响我们管理这些令人衰弱的疾病的方式的现实世界变化。问题是，计算工具通常是在定制的研究数据集上开发和测试的，这些数据与NHS常规收集的数据几乎没有相似之处。该项目旨在消除解锁人工智能对痴呆症现实世界影响的主要障碍：研究人员访问从记忆诊所常规收集的数据，这是痴呆症医疗保健的前线。大型医学研究数据集的日益可用创造了无数机会和人工智能提供旨在早期诊断和准确预后的量化解决方案的例子(Marinescu，Melba 2021)。然而，这种定制的、高质量的研究数据很少能代表常规收集的医疗数据。人工智能技术开发人员与痴呆症医疗保健第一线之间的这种根本脱节是阻止现实世界影响的关键障碍。我们的解决方案是将开发人员与常规收集的数据联系起来。记忆诊所代表了痴呆症医疗服务的第一线，也是原型解决方案的理想环境。我们提供了两种解决方案：一种是将匿名数据传输给人工智能研究人员，另一种是将人工智能算法直接用于数据。

Dementias affect over 55 million people worldwide and will exceed 135 million by 2050. This age-related global pandemic-in-waiting is an ideal application for AI to affect real-world change in how we manage these debilitating illnesses. The problem is that computational tools are typically developed and tested on bespoke research datasets that bear little to no resemblance to the data that is routinely collected in the NHS. This project aims to remove the primary roadblock to unlocking AI for real-world impact in the dementias: researcher access to routinely collected data from Memory Clinics, the front line in dementia healthcare.The increasing availability of large medical research datasets has created myriad opportunities and examples of AI providing quantitative solutions targeting early diagnosis and accurate prognosis (Marinescu, MELBA 2021). However, such bespoke, high quality research data is rarely representative of routinely collected healthcare data. This fundamental disconnection between AI technology developers and the frontline of dementia healthcare is a key roadblock preventing real-world impact.Our solution is to connect developers with routinely collected data. Memory clinics represent the frontline of dementia healthcare services and are the ideal setting for prototyping solutions.We provide two solutions: one involves transferring anonymous data to the AI researchers, the other takes the AI algorithms directly to the data.