AI4LIFE

Artificial Intelligence for Image Data Analysis in the Life Sciences

Grant period2022-09-01 - 2025-08-31
Funding bodyEuropean Union
Call numberHORIZON-INFRA-2021-SERV-01
Grant number101057970
IdentifierG:(EU-Grant)101057970

Note: Machine learning (ML) has enabled and accelerated frontier research in the life sciences, but democratised access to such methods is, unfortunately, not a given. Access to necessary hardware and software, knowledge and training, is limited, while methods are typically insufficiently documented and hard to find. Furthermore, even though modern AI-based methods typically generalize well to unseen data, no standard exists to enable sharing and fine-tuning of pretrained models between different analysis tools. Existing user-facing platforms operate entirely independently from each other, often failing to comply with FAIR data and Open Science standards. The field of AI and ML is developing at a staggering pace, making it impossible for the non-specialist to stay up to date. To enable the life science communities to benefit from AI/ML-powered image analysis methods, AI4LIFE will build bridges, providing urgently needed services on the common European research infrastructures. We will build an open, accessible, community-driven repository of FAIR pre-trained AI models and develop services to deliver these models to life scientists, including those without substantial computational expertise. Our direct support and ample training activities will prepare life scientists for responsible use of AI methods, while contributor services and open standards will drive community contributions of new models and interoperability between analysis tools. Open calls and public challenges will provide state-of-the-art solutions to yet unsolved image analysis problems in the life sciences. Our consortium brings together AI/ML researchers, developers of popular open source image analysis tools, providers of European-scale storage and compute services and European life sciences Research Infrastructures -- all united behind the common goal to enable life scientists to fully benefit from the untapped but potentially tremendous power of AI-based analysis methods.
   

Recent Publications

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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings/Journal Article  ;  ;  ;  ;
Towards an integrated plant phenotyping – technology, data, community
2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), PisaPisa, Italy, 6 Nov 2023 - 8 Nov 20232023-11-062023-11-08 Proceedings of the IEEE 1, 36-40 () [10.1109/MetroAgriFor58484.2023.10424266] BibTeX | EndNote: XML, Text | RIS

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 Record created 2023-02-22, last modified 2023-02-22



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