The National Institute for Health Research (NIHR) invites proposals to undertake programmes of research to spearhead the use of artificial intelligence (AI) methods to develop insights for the identification and subsequent prevention of multiple long-term conditions (multimorbidity) or MLTC-M.
Research funded through this initiative will use AI and data science methods, combined with expertise in clinical practice, applied health and care research and social science, to systematically identify or explore clusters of disease. In addition to the identification and mapping of new clusters of disease, the call seeks research to better understand the trajectories of patients with MLTC-M over time and throughout the life course, including the influence of wider determinants such as environmental, behavioural and psychosocial factors.
This competition aims to bring together multi-disciplinary Research Collaborations to build on our existing understanding of disease clusters in people with MLTC-M using ground-breaking AI techniques; and to grow capability for multi-disciplinary working in this crucial research area.
In order to facilitate new collaborations and build capability, this call has a two-stream approach.
We reserve the right to open the Wave 2 call to new Research Collaboration applicants. This decision will be made after the funders have reviewed the responses and funding awards made at Wave 1.
We are planning to hold a networking and engagement event on the 17th July. Further details will be released shortly. Please register your interest in the event here.
General enquiries regarding the application and commissioning process can be directed to the AIM Team via the online form. Please ensure that you leave a contactable phone number and a member of the team will get back to you.
Please note: the Research Management System (RMS) will be available next week for applications (Tuesday 07 July 2020), but in the meantime please use the template word application forms to refer to (these can found under ‘Supporting Information’).
Article Source: https://www.nihr.ac.uk/