ELIXIR industry event: machine learning and AI in life science research

ELIXIR Innovation and SME Forum: AI in health research

On 13 April, ELIXIR and ELIXIR Netherlands held an Innovation and SME Forum focusing on machine learning and artificial intelligence (AI) in health research with more than 60 participants from industry and academia.

The forum started with a welcome talk from Ruben Kok, the technical coordinator of ELIXIR Netherlands and Director of DTL, detailing the mission of Health-RI and its connection with ELIXIR. Following Ruebn’s talk, Cor Veenman, the Lead Scientist of the TNO artificial intelligence program, gave an in-depth talk about what AI can bring to health innovation and emphasised the importance of federated decisions, transparency of research and building trust with the public.

To address the successes and struggles in adopting AI technology in health research and life sciences, ELIXIR invited speakers from different sectors to share their perspectives, including a large enterprise (IQVIA), a small to medium enterprise (Roseman Labs), an investor (BOM) and academia (Erasmus MC). The panel discussion focused on improving the ecosystem of AI in health research and boosting innovation at both national and European levels. The panellists mentioned the acceleration of European health research with the European Health Data Space and the importance of standards on data sharing.

During the flash talk session and the roundtable discussion, representatives from SME and start-up companies presented their achievements as well as the challenges they faced and the partnerships they are seeking. 

Developing standards and frameworks 

The forum added to the body of expertise in machine learning and AI in ELIXIR, centred around the ELIXIR Machine Learning Focus Group. Recently, ELIXIR authors published a chapter on defining machine learning standards in life sciences in the book ‘Artificial Intelligence for Science: A Deep Learning Revolution.  This year, a new ELIXIR-funded study was initiated, ‘A framework to standardise machine learning in life sciences’ aiming to increase the adoption and overall impact of the DOME (data, optimization, model and model and evaluation) recommendation within and beyond ELIXIR.

Machine learning and AI look set to play an important role in life sciences in the coming years. ELIXIR will continue to work with a range of partners to promote the development and exploitation of the technology for the benefit of European citizens.

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