Working groups and SIGs
Focused communities for developing shared questions, methods, and practical guidance in health data science.
Community
Researchers, clinicians, students, and partners come together through shared projects, practical learning, and open exchange.
Activities and platform
ISFHDS supports formats that make methods easier to test, teach, and translate across institutions and disciplines.
Focused communities for developing shared questions, methods, and practical guidance in health data science.
Reference implementations for reproducible data curation, modelling, evaluation, and analytical workflows.
Transparent comparisons built around clear provenance, licensing, evaluation cards, and reproducibility checks.
Workshops, tutorials, and summer-school formats with hands-on learning for students, researchers, and practitioners.
Space for interdisciplinary discussion, peer learning, and connections across career stages.
Opportunities to compare methods and evidence across settings while respecting local governance and data constraints.
Affiliated initiative
GenAIMed is a collaborative group focused on generative AI for medicine and the life sciences.
The group connects researchers exploring large language models and other generative systems in medical and life-science research.
Its focus on rigorous evaluation and responsible use of generative models complements the Society’s wider mission across clinical and research settings.
Social impact
Health data science should serve diverse communities and produce evidence that can inform practice, education, and policy.
Examine performance across demographic groups and incorporate measures informed by social determinants of health.
Share curricula and practical resources that support responsible workforce development.
Translate evidence into clear briefs and contribute technical expertise to standards discussions.
Get involved
Tell us about your area of work and how you would like to contribute to the ISFHDS community.