R&D Projects

Avert

The AVERT project is a collaboration between Mersey Care, the UK largest Mental Health Trust, Kings College London (KCL), The University of Liverpool (UoL) and AIMES. The project aims to use AI technologies to predict the onset of crisis and the impact of healthcare interventions for mental health service users. 

The project builds upon a very successful feasibility project funded by Innovate UK between 2018 and 2020 and has the potential to transform the treatment and care of mental health patients by predicting and averting crisis rather than by simply reacting. This preliminary work has ingested over 12 years’ worth of NHS clinical data from Mersey Care and generated over 4 billion annotations using natural language processing technology developed by Professor Dobson at KCL.  These annotations have been used by Professor Maskill at UoL to create ML algorithms which predict descent into crisis and the interventions most likely to prevent this. The data and analysis has been carried out in a highly secure, NHS accredited facility at AIMES and patients and clinical staff have been directly involved in the project from the outset – in terms of engagement/evaluation around issues such as consent, specificity/sensitivity, usability and trust. The patient and clinician forums have proved fundamental to the progress made to date.



The key tasks to be undertaken during next phase of the project are;

  • Clinical validation of the algorithm(s) to fully understand the safety and efficacy of the predictors and indicators of intervention. Work has initially been undertaken to validate the AVERT infrastructure and software to both FDA and CE standards Health economic modelling (using the NICE Framework) to more fully understand the financial implications of a preventative approach to mental health care – by predicting crisis and intervening in an effective way, what are the cost savings?
  • We need to work with clinicians and patients on developing human interfaces to the AVERT platform to show how predicting crisis will be incorporated into the care pathway.  Mersey Care have a national/international reputation for care innovation and transformation (including the “Zero Suicide Alliance” and the “Life Rooms” programmes) and are committed to developing new pathways based upon predictive rather than reactive care and to move towards individual/personalized interventions.


The AVERT project will deliver two important outcomes;

1. A set of clinically evaluated AI algorithms to predict crisis and personalized interventions from unstructured mental health data. These algorithms will be available to the NHS as both web services and as licensed technologies within EPR platform

2. A large-scale training and testing data set, richly annotated which can be used to create predictive algorithms across a range of mental health conditions and treatment interventions.

OpenCARE

OpenCARE

OpenCARE is a collaboration between AIMES, University College London and Barts Health NHS Trust to better measure heart function using AI in imaging. Working with world leading cardiac imaging and data science expertise, (Prof James Moon and Dr Rhodri Davies) we’re able to demonstrate more precise measurement of the heart, by automatically segmenting MRI scans and providing the results instantly to clinicians and researchers. We have developed AI models around Left Ventricular Ejection Fraction, Arterial Flow Analysis and accessory pathway localisation with more models in the pipeline.

 OpenCARE has been trained on over 2m images from 2000 consenting patients across the world.

 http://test.opencare.health

 OpenCARE is available via the OpenCARE Portal or OpenCARE TRE also via our channel partners.

MUSA

MUSA
AIMES are collaborating with a number of the leading technology institutions in both the public and private sector for MUSA, the Multi-cloud Secure Application. The main objective of MUSA is to support management of applications over diverse cloud resources, through a security framework which includes security-by-design mechanisms which allow application protection at runtime, and tools for the integrated security assurance in both the engineering and operation of multi-cloud applications. The MUSA framework leverages security-by-design, agile and DevOps approaches in multi-cloud applications, and enables the security-aware development and operation of multi-cloud applications.

www.cloudwatchhub.eu/serviceoffers/musa-multi-cloud-secure-applications

www.musa-project.eu

© 2017 - MUSA This Project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644429

SHiELD

SHiELD
SHiELD, or the European Security in Health Data Exchange, is a European funded Horizon 2020 project which facilitates the secure exchange of health data across borders. The project’s aim is to protect health data whilst patients travel abroad, assisting in a smooth data exchange across geographical boundaries in the event that it is necessary. By uniting health authorities from Lancashire, the Basque country, and Milan, SHiELD has demonstrated how data is to be safely transferred.

www.project-shield.eu/

© 2017 - SHiELD - This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 727301

DECIDE

DECIDE
Decide is a Horizon 2020 funded project focusing on development operations for trusted and interoperable multi-cloud application towards the digital single market. The aim of Decide is to provide a framework of multi-cloud service-based software which allows clients to design and develop applications in a reliable, interoperable and legally compliant environment. AIMES specialises in e-Health, making it the perfect environment for those operating in the DevOps paradigm.

www.decide-h2020.eu/

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731533

ASSURED

After being awarded funding from Innovate UK’s Protecting Data in Industry competition, AIMES partnered with Metrarc and The University of Southampton IT Innovation Centre to develop ASSURED: Automated Security for Supplier-User Reference models in E-health Data. This project will accelerate access to data for organizations that operate secure platforms in the health supply chain and it will enable institutions to automatically identify threats to their networks. Additionally, ASSURED will speed up the approval process to the N3 network by enabling continuous automated verification.

Connected Health Cities

Connected Health Cities
AIMES is working together with the Innovation Agency, The University of Liverpool and Lancaster University to deliver the Connected Health Cities project. The Connected Health Cities project utilises Northwest patient data to focus on three key areas; alcohol misuse, epilepsy and COPD. The collection of this data allows for medical specialists to access uptodate patient data, enabling them to review and develop the care that they offer. Eventually, this project aims to apply innovation and efficiency to healthcare in the North-West, through data-analysis and research.

https://www.connectedhealthcities.org/

PIBD-SET Quality

PIBD-SET Quality (Paediatric Inflammatory Bowel Diseases Network for Safety, Efficacy, Treatment and Quality improvement of care ) is a Horizon 2020 funded project, which started in January 2016. The overall goal of this proposal was to develop and validate an algorithm for PIBD, based on high or low risk predictors, which detect early complicated or relapsing disease. This will improve effectiveness, reducing treatment related risks and life-long complications due to uncontrolled disease progression.

AIMES provide a secure and compliant hosting environment, where cohort data is stored and documentation between the European Network can be shared. Project partners include NHS Glasgow, Queen Mary University London, Paris Descartes and Shaare Zedek Medical Center of Isreal.