Personal profile
Introductory remarks on publicationslist
For a full list of publications please visit https://adrianzucco.com/publication/
Short presentation
I’m a curious researcher passionate about untangling the complexity of our inner experiences and the intricate world around us, all with the aim of enhancing our health and well-being. My interests span multiple levels:
- Methodologically, I focus on applying explainable machine learning as a scientific tool to model complexity. Specifically, within the realm of public health and epidemiology, these tools hold the potential to uncover patterns, mechanisms, and dynamics of diseases arising from the interplay of diverse biopsychosocial factors.
- Academically, I have contributed to the fields of bioinformatics, immunology, and infectious diseases (mainly HIV and COVID-19). More recently, I have broadened my scope to explore how mental health and societal factors contribute to or moderate the onset of diseases.
- On a personal level, I strive to challenge and overcome limiting assumptions in statistics and biomedical research by integrating interdisciplinary insights from philosophy, cognitive and contemplative science, causal inference, artificial intelligence, and complexity science.
- Socially, I advocate for open-source and reproducible research. I also actively explore innovative formats for scientific communication and teaching to the general public.
Education/Academic qualification
Biostatistics and Bioinformatics, PhD, Explainable Machine Learning for Precision Medicine of Patients with Infectious Diseases
Award Date: 5 Dec 2022
Bioinformatics and Systems Biology, MSc
Biochemistry, BSc, Specialization in Molecular Biomedicine
Collaborations and top research areas from the last five years
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Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Zucco, A. G., Agius, R., Svanberg, R., Moestrup, K. S., Marandi, R. Z., MacPherson, C. R., Lundgren, J., Ostrowski, S. R. & Niemann, C. U., 2022, In: Scientific Reports. 12, 13879.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile6 Citations (Scopus)84 Downloads (Pure) -
Explainable machine learning for precision medicine of patients with infectious diseases
Zucco, A. G., 2022, Copenhagen: University of Copenhagen, Faculty of Health and Medical Sciences. 111 p.Research output: Ph.D Thesis › Ph.D. Thesis
Open AccessFile73 Downloads (Pure) -
Associations of functional human leucocyte antigen class I groups with HIV viral load in a heterogeneous cohort
Zucco, A. G., Bennedbæk, M., Ekenberg, C., Gabrielaite, M., Leung, P., Polizzotto, M. N., Kan, V., Murray, D. D., Lundgren, J. D., MacPherson, C. R. & INSIGHT START Study Group, 2023, In: AIDS. 37, 11, p. 1643-1650 8 p.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile2 Citations (Scopus)67 Downloads (Pure) -
Patterns of registered and self-reported sleep problems in young adults with different histories of childhood adversity
Echterhoff, J., de Vries, T. R., Zucco, A. G., Strandberg-Larsen, K., Kriston, L. & Rod, N. H., 2026, PsyArXiv, 18 p.Research output: Working paper › Preprint
File3 Downloads (Pure) -
The Young Adult Sleep model: an evolving causal loop diagram of mental health dynamics
Uleman, J. F., Al-Shama, R. F. M., Zucco, A. G., Echterhoff, J., Luijten, M., Verhagen, M., Vyrastekova, J., Treur, J. L., Wootton, R. E., Jones, S., Dresler, M., Drews, H. J., Egebjerg, C., Kornum, B. R., Stronks, K. & Rod, N. H., 2026, In: BMC Medicine. 24, 1, 16 p., 159.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile10 Downloads (Pure) -
Complex models, marginal benefits--a multi-centre development and validation study of early warning scores across 2.16 million patient admissions addressing intercurrent medical interventions
Katsiferis, A., Scheidwasser, N., Nguyen, T., Lange, T., MP, K., PB, N., KK, I., CS, M., EK, A., Moelgaard, J., AG, Z., TV, V. & Bhatt, S., 2025, medRxiv, 21 p.Research output: Working paper › Preprint
File3 Downloads (Pure) -
Dynamics of childhood adversity and poor physical and mental health in children experiencing high adversity: Findings from the DANLIFE cohort
Tjeerd Rudmer Vries, D., Elsenburg, L. K., Bennetsen, S. K., Zucco, A. G. & Rod, N. H., 2025, PsyArXiv, 30 p.Research output: Working paper › Preprint
File3 Downloads (Pure) -
Exploring nationwide patterns of sleep problems from late adolescence to adulthood using machine learning
Zucco, A. G., Drews, H. J., Uleman, J. F., Bhatt, S. & Rod, N. H., 2025, In: Science Advances. 11, 39, 10 p., eadw1227.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile1 Citation (Scopus)32 Downloads (Pure)