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AI Healthcare Network Seed Funding

The UCD Institute for Discovery, through the AI Healthcare Hub, announce the winners of the inaugural AI Healthcare Network Seed funding. Seed funding was awarded to 5 winning networks of interdisciplinary collaborators led by a core lead in UCD, aiming to develop approaches and applications to support implementation of responsible AI to address urgent, timely problems.

Funded Networks

This network of leading figures in Irish health innovation seeks to bridge the domains of medicine, computer science and design to realise increasingly inclusive cultures and accessible practices of responsible AI Healthcare innovation.\n Inclusive Design for AI Healthcare Innovation Network
This network of leading figures in Irish health innovation seeks to bridge the domains of medicine, computer science and design to realise increasingly inclusive cultures and accessible practices of responsible AI Healthcare innovation.
The network aims to leverage the recent advances in AI to accelerate and advance the study of the abdominal wall with the aim of identifying risk factors for hernia recurrence and ultimately reducing the recurrence rate. AI & Dynamic MRI to Assess Abdominal Hernias
The network aims to leverage the recent advances in AI to accelerate and advance the study of the abdominal wall with the aim of identifying risk factors for hernia recurrence and ultimately reducing the recurrence rate.
Our network aims to build on our existing work with Siamese U Transformers for change detection on MRI in Multiple Sclerosis, to help deliver faster and more accurate diagnoses for people with MS. Transforming the Imaging of Multiple Sclerosis with AI
Our network aims to build on our existing work with Siamese U Transformers for change detection on MRI in Multiple Sclerosis, to help deliver faster and more accurate diagnoses for people with MS.
The network aims to collect data on the impact of AI reconstruction tools in clinical imaging and act as a platform for establishing a national interdisciplinary network of radiographers, medical physicists and radiologists. CT Interprofessional Network for AI Reconstruction (CT-IN-AIR)
The network aims to collect data on the impact of AI reconstruction tools in clinical imaging and act as a platform for establishing a national interdisciplinary network of radiographers, medical physicists and radiologists.
This network aims to pursue a preliminary investigation into which aspects of mental health chatbots are perceived as useful together with whether or not users are able to identify potential harms of such applications. Public Trust for GenAI in Mental Health Care
This network aims to pursue a preliminary investigation into which aspects of mental health chatbots are perceived as useful together with whether or not users are able to identify potential harms of such applications.

Call Details

Details of the seed funding

This program brings together international experts from across academia, civil society, government, and industry to drive sector-specific practice and action by developing and implementing solutions using responsible AI.

The successful projects will involve a network of interdisciplinary collaborators led by a core group of up to six individuals. Each team works to develop approaches and applications to support implementation of responsible AI to address urgent, timely problems.

Award Amount

The initial seed funding award will be up to 4,000 euros per successful project to support costs directly associated with advancing the network’s ambition.  Seed funding will initially be awarded for one year. 

Additional Support

In addition to the seed funding award, successful candidates will become Discovery Fellows and will have access to:

  • Additional logistical support to enable a minimum of two interactions per year (in-person or virtually) between members of the network and external experts.
  • UCD Discovery’s programmatic and administrative support

Proposals will be evaluated based on proposed network composition and planned outputs.

Planned network outputs may include:

  • Research Workshop, Conference, Symposium
  • Themed networking event
  • A preliminary grant proposal
  • A joint research publication
  • A publication directed toward non-academic audiences such as policymakers and NGOs
  • Podcasts or other media content

The proposed network should be made up of an interdisciplinary and cross-sectoral team and should:

  • be led by two co-directors and can be composed of additional members of any level including PhD students. 
  • include at least one computer/data scientist.
  • include at least one medical sciences expert.
  • achieve equity, diversity and inclusion in the team composition.

Proposals with expertise in legal, ethical or policy implication of AI will be favourably received.

Application procedure

*Applications have now closed.*

Proposals related to any aspect of the intersection of AI and health are welcome.

The application deadline is 5pm, 15 June 2024.

UCD Institute for Discovery

O'Brien Centre for Science, Belfield, Dublin, Ireland.
E: discovery@ucd.ie | Location Map(opens in a new window)

www.ucd.ie/discovery