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Center for Health Data Science publications

Updated: 2023-03-28

HeaDS believes in the principles of open science and reproducibility. As part of our commitment to these values, we strive to make our publications as reproducible as possible. To achieve this, we make our research process transparent by showcasing the GitHub repositories that contain our code and data. We also document our research process to ensure that others can replicate our findings and build upon them. By doing so, we hope to contribute to the wider scientific community's efforts to promote openness and transparency in research.

Krogh group

Anders Krogh

Head of HeaDS / Group Leader / Professor

Iñigo Prada Luengo


Viktoria Schuster

PhD Student

The deep generative decoder: Using MAP estimates of representations

DGD is a package for probabilistic representation learning. It can be applied to various tasks. The implementation for Fashion-MNIST and single-cell expression counts can be found in branch paper.

Karaderi group

Tugce Karaderi

Group Leader / Assistant Professor

Chloe Pittman

PhD Student

Yengo, L., Vedantam, S., Marouli, E. et al. A saturated map of common genetic variants associated with human height. Nature 610, 704-71 (2022).

Collin CB, Gebhardt T, Golebiewski M, Karaderi T, Hillemanns M, Khan FM, Salehzadeh-Yazdi A, Kirschner M, Krobitsch S, EU-STANDS4PM consortium, Kuepfer L. Computational Models for Clinical Applications in Personalized Medicine-Guidelines and Recommendations for Data Integration and Model Validation. Journal of Personalized Medicine. 2022; 12(2):166.

Barin Burc, Yoldascan Banu Elcin, Savaskan Fatma, Ozbalikci Goncagul, Karaderi Tugce, Çakal Hüseyin. Joint Investigation of 2-Month Post-diagnosis IgG Antibody Levels and Psychological Measures for Assessing Longer Term Multi-Faceted Recovery Among COVID-19 Cases in Northern Cyprus. Front. Public Health. Volume 8 - 2021.

Last update: July 6, 2023
Created: July 6, 2023