Data models for dynamic precision medicine
Martin Bøgsted, professor in bioinformatics and statistics, Department of Clinical Medicine, Aalborg University and Department of Haematology, Aalborg University Hospital
Precision medicine holds the promise to improve quality of life of patients and reduce health care costs by artificial intelligence applied on integrated clinical and genomic information. In particular, patients expect to obtain precision medicine throughout their entire disease course. This requires application of dynamic predictive models based on heterogeneous patient information. Based on literature and our own research, we will illustrate the limitations and potential of the Danish administrative and clinical databases to facilitate dynamic precision medicine. In particular, we will discuss the requirements for future data collection in order to fulfil the vision of dynamic precision medicine and reduced health care costs.
Martin Bøgsted is professor in bioinformatics and statistics at Department of Clinical Medicine, Aalborg University and Department of Haematology, Aalborg University Hospital. His primary research focus is on translating high throughput biological and big clinical data findings to clinical practice. Therefore, his research has spanned from data base construction, machine learning, and high performance computing to clinical applications within cancer. He is responsible for of implementing the bioinformatics workflow of precision medicine at Aalborg University Hospital as well as national coordinator of NEXT Bioinformatics, and member of the Research and Infrastructure Committee under the Danish National Genome Centre.