Lab profile
About CDS
Clinical Data Science is a joint academic department focused on developing global FAIR federated health data sharing infrastructures, using artificial intelligence methods to learn from health data, and applying AI to improve health outcomes. The department brings together scientists, engineers, and staff from diverse backgrounds to work on data-driven healthcare research and implementation.
01 · Research focus
Research areas and highlights
Topics and recent work as stated on the lab’s own site.
- AI RendsArtificial intelligence decision support for oropharyngeal carcinoma to determine if patients can be spared from neck dissection surgery.
- AIDAVAAI powered data curation virtual assistant.
- AIM@EpilepsyA living CML guideline within the CMyLife platform.
- AMICUSAI in Medical Imaging for novel Cancer User Support.
- CARRIERCoronary artery disease risk estimations and interventions for prevention and early detection using Personal Health Train.
- CMyGuidelineA living chronic myeloid leukaemia guideline within the CMyLife platform.
- CODACenter for Ophthalmology Data Analytics at Aravind.
- DigiONEDigital Oncology Network for Europe.
- Health-AISystem breakthrough project to revolutionize how AI is developed and validated in health.
- Health-RIEnabling data driven health.
- PersOnExplainable, maintainable, and trustworthy decision support systems for personalized care in oncology.
- PRE-ACTPrediction of radiotherapy side effects using explainable AI.
02 · People
Leadership and researchers
People listed on the lab’s team pages, by role.
03 · Research intelligence
Research Intelligence evidence
Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.
Publications & preprints
- AI Model Reporting Standards in Health Care: Systematic Review and Consolidation.JMIR AI · 2026
- SMART: structured, meaningful, auditable, responsible, and transparent documentation for clinical AI.Journal of the American Medical Informatics Association : JAMIA · 2026
- Center-specific Federated Learning for Radiation Pneumonitis:A Cross-Center Adaptive Alternating Framework.International journal of radiation oncology, biology, physics · 2026
Clinical-trial records
- Deep Learning Model Predicts Pathological Complete Response of Lung Cancer Following Neoadjuvant ImmunochemotherapyNCT06285058 · Status unknown
04 · Updates
Updates and lab news
News and events from the lab’s own site.
No news has been collected from the lab’s site yet.
05 · Official presence
Lab sources and channels
The lab’s own pages and accounts.
06 · Related
Related labs and centers
Labs at the same institution and labs working on similar topics.