Projects per year
Personal profile
Research
My overarching goal is to turn health data into clinical insights and applications by using advanced statistical and machine learning (ML) methods. More specifically, my lab works on the development and application of ML methods to be able to integrate clinical data of different types in risk prediction of diabetic complications. We are doing so while actively listening to the users’ voices and by building bridges between clinicians and the data science community.
Profile
I am an applied mathematician by training with a PhD and 15 years of experience in diabetes epidemiology. Having worked in five countries around the world and taught in four languages, I have a strong focus on internationalization and creating an attractive interdisciplinary research environment. I am leading the Machine Learning & Clinical Prediction Lab, where we collaborate across disciplines. I am currently pursuing an Executive MBA degree to gain more skills in leadership, strategy and innovation.
Areas of expertise
- Diabetes
- Machine learning
- Artificial intelligence
- Epidemiology
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Collaborations and top research areas from the last five years
Projects
- 2 Active
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Integration of fundus photographs in risk assessment of cardiovascular disease using deep learning
Li, L. (PI), Hulman, A. (PI), Byberg, S. (Collaborator) & Thambawita, V. (Collaborator)
01/08/2023 → 31/07/2026
Project: Research
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Integration of longitudinal multimodal data in clinical risk prediction using deep learning
Hulman, A. (PI)
01/04/2023 → 31/03/2028
Project: Research
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Effect of gestational diabetes on fetal growth rate and later overweight in the offspring
Leth-Møller, M., Hulman, A., Kampmann, U., Hede, S., Ovesen, P. G. & Knorr, S., 25 Jun 2024, (E-pub / Early view) In: The Journal of clinical endocrinology and metabolism.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
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Hemoglobin A1c Trajectories During Pregnancy and Adverse Outcomes in Women With Type 2 Diabetes: A Danish National Population-Based Cohort Study
Koefoed, A. S., Knorr, S., Fuglsang, J., Leth-Møller, M., Hulman, A., Jensen, D. M., Andersen, L. L. T., Rosbach, A. E., Damm, P., Mathiesen, E. R., Sørensen, A., Christensen, T. T., McIntyre, H. D., Ovesen, P. & Kampmann, U., Jul 2024, In: Diabetes Care. 47, 7, p. 1211-1219 9 p.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
Open Access -
Heterogeneity in glycaemic control in children and adolescents with type 1 diabetes: A latent class trajectory analysis of Danish nationwide data
Wibaek, R., Ibfelt, E. H., Andersen, G. S., Hulman, A., Dabelea, D., Jørgensen, M. E., Svensson, J., Vistisen, D. & Rønn, P. F., Mar 2024, In: Diabetic medicine : a journal of the British Diabetic Association. 41, 3, 10 p., e15275.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
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Prediction of cardiovascular markers and diseases using retinal fundus images and deep learning: a systematic scoping review
Li, L. Y., Isaksen, A. A., Lebiecka-Johansen, B., Funck, K., Thambawita, V., Byberg, S., Andersen, T. H., Norgaard, O. & Hulman, A., 1 Nov 2024, In: European Heart Journal - Digital Health. 5, 6, p. 660-669 10 p.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Review › Research › peer-review
Open Access -
SuperLearner based prediction of fetal growth restriction in a Danish national birth cohort
Thunbo, M. Ø., Hulman, A., Witte, D. R., Liew, Z. & Pedersen, L. H., 19 Nov 2024.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
Activities
- 1 Employment and shares in external organisations
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Hulman Consulting (privately owned company)
Hulman, A. (Lecturer)
2023 → …Activity: Presentations, memberships, ownership and other activities › Employment and shares in external organisations