Machine learning with a clinical purpose
The Hulman Lab is an interdisciplinary researcher group in machine learning and clinical prediction at Steno Diabetes Center Aarhus, affiliated to the Department of Public Health at Aarhus University, Denmark. We share a passion for data science and believe that applying machine learning methods to multimodal data from epidemiological cohorts and the healthcare sector can provide clinical insights and more comprehensive profiling of disease risk.
Our group members represent a wide range of scientific profiles from data science, mathematics to sport science and medicine. We aim to combine our skills in interdisciplinary projects and then communicate our findings to both research communities.
Machine learning methods can help us to transfer knowledge between domains, e.g. from epidemiology to clinical research. We aim to repurpose models developed in epidemiological cohorts with deep phenotyping into clinical tools based on clinical cohorts with routinely collected information and linkages to the Danish registries.
We are based at a Danish hospital, which gives us valuable insights into the healthcare system. We aim to identify relevant needs and develop data-driven tools to tackle these challenges. In this process, beyond the scientific community, we interact with stakeholders, clinicians and patients.