Joel works as Data director to the Center for Medical Image Science and Visualization (CMIV) and the Analytical Imaging Diagnostics Arena (AIDA), which is a collaboration arena supporting research and innovation in Artificial Intelligence (AI) in medical imaging diagnostics.
In this position Joel heads up the NBIS unit AIDA Data Hub, which is a data infrastructure supporting AIDA with services for data sharing and high performance AI training on sensitive personal medical imaging data for research. Joel also leads the repository infrastructure development in the Bigpicture effort to establish a Petabyte AI platform for European digital pathology. Joel also heads up the efforts at AIDA Data Hub to provide similar data collaboration services for the European Cancer Imaging federation (EUCAIM), and for the ASHA effort to build Health Data Spaces for primary and secondary use of health data in open standards in collaboration between Linköping University, four regional healthcare providers, major providers of health record systems, and startup companies in multi-omic and multi-modal diagnostics of complex multisystemic diseases including long covid. Joel is also engaging in the SciLifeLab Linköping Infrastructure Group and the NAISS Sensitive data procurement group for the next flagship comute system Arrhenius, and as the Linköping Univerity data contact to the SciLifeLab & Wallenberg national program for Data-Driven Life Science (DDLS).
Previously, as a Ph d and application expert in bioinformatics at the National Supercomputer Centre (NSC), Joel engaged as an Executive in the formative years of the Nordic e-Infrastructure Collaboration (NeIC), and was part of initiating and running its Tryggve series of projects supporting transnational research on sensitive personal biomedical data together with the Nordic nodes of ELIXIR.
Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden. J Hedlund, A Eklund, C Lundström Scientific Data, 2020
Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposal J Olczak, J Pavlopoulos, J Prijs, FFA Ijpma, JN Doornberg, C Lundström, J Hedlund, M Gordon Acta orthopaedica, 2021
Medium- and short-chain dehydrogenase/reductase gene and protein families: the MDR superfamily B Persson, J Hedlund, H Jörnvall Cellular and molecular life sciences, 2008
Superfamilies SDR and MDR: from early ancestry to present forms. Emergence of three lines, a Zn-metalloenzyme, and distinct variabilities H Jörnvall, J Hedlund, T Bergman, U Oppermann, B Persson Biochemical and biophysical research communications, 2010
Quantitative membrane proteomics applying narrow range peptide isoelectric focusing for studies of small cell lung cancer resistance mechanisms H Eriksson, J Lengqvist, J Hedlund, K Uhlén, LM Orre, B Bjellqvist, B Persson, J Lehtiö, PJ Jakobsson Proteomics, 2008
BRICHOS-a superfamily of multidomain proteins with diverse functions. J Hedlund, J Johansson, B Persson BMC research notes, 2009