92 citations · 107 across the 5 of their papers we have counts for
5 papers
An ELIXIR scoping review on domain-specific evaluation metrics for synthetic data in life sciences
Styliani-Christina Fragkouli, Somya Iqbal, Lisa Crossman +11
Synthetic data has emerged as a powerful resource in life sciences, offering solutions for data scarcity, privacy protection and accessibility constraints. By creating artificial d…
Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences (October 2025 -- Version 2)
Gavin Farrell, Eleni Adamidi, Rafael Andrade Buono +27
Artificial intelligence (AI) has recently seen transformative breakthroughs in the life sciences, expanding possibilities for researchers to interpret biological information at an…
DOME Registry: Implementing community-wide recommendations for reporting supervised machine learning in biology
Omar Abdelghani Attafi, Damiano Clementel, Konstantinos Kyritsis +17
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The DOME recommendations aim to enhance the validation and reproducibility of ML resea…
Synthetic data: How could it be used for infectious disease research?
Styliani-Christina Fragkouli, Dhwani Solanki, Leyla J Castro +4
Over the last three to five years, it has become possible to generate machine learning synthetic data for healthcare-related uses. However, concerns have been raised about potentia…
FAIR for AI: An interdisciplinary and international community building perspective
E. A. Huerta, Ben Blaiszik, L. Catherine Brinson +21
A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with th…