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

基于常规收集的数据，为人工智能痴呆症研究试点安全、可扩展的基础设施

基本信息

批准号：
MR/X005674/1
负责人：
Neil Oxtoby
金额：
$ 20.13万
依托单位：
University College London
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=MR%2FX005674%2F1
关键词：
Piloting Secure Scalable Infrastructure AI

项目摘要

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.

痴呆症影响全世界超过5500万人，到2050年将超过1.35亿人。这种与年龄相关的全球流行病是人工智能影响现实世界改变我们如何管理这些使人衰弱的疾病的理想应用。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，这些数据集与NHS定期收集的数据几乎没有相似之处。该项目旨在消除解锁AI对痴呆症现实世界影响的主要障碍：研究人员可以访问痴呆症医疗保健前线记忆诊所定期收集的数据。大型医学研究数据集的日益可用性为AI提供针对早期诊断和准确预后的定量解决方案创造了无数机会和例子（Marinescu，MELBA 2021）。然而，这种定制的高质量研究数据很少能代表常规收集的医疗保健数据。人工智能技术开发人员与痴呆症医疗保健前线之间的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前沿，是原型解决方案的理想场所。我们提供两种解决方案：一种是将匿名数据传输给AI研究人员，另一种是将AI算法直接用于数据。