Prof. Dr. rer. hum. biol. Björn-Hergen Laabs

Head of Working Group „Statistical Evidence in AI Systems“

telephone: +49 551 3964064

fax: +49 551 3965605

e-mail address:bjoern-hergen.laabs(at)med.uni-goettingen.de

location: Humboldtallee 32, EG 141

ORCID ID: orcid.org/0000-0002-9265-5738

Short biography

[since 2025]
UMG Göttingen, Department of Medical Statistics, Assistant Professor (W1ttW2)

[2022 - 2025]
University of Lübeck, Institute of Medical Biometry and Statistics, Postdoctoral Researcher

[2017 - 2022]
University of Lübeck, Institute of Medical Biometry and Statistics, Doctoral Researcher

[2015 - 2017]
M.Sc. Computational Life Sciences, University of Lübeck

[2012 - 2015]
B.Sc. Computational Life Sciences, University of Lübeck

Research interests

  • Interpretability of AI models (explainable AI)
  • Quantification of Uncertainty in prediction models
  • Causal inference in AI systems
  • Reduced penetrance of neurological movement disorders 

Involvement in professional societies

[since 2024]
Member of the „Deutschen Gesellschaft für Informatik, Biometrie und Epidemiologie e.V.“ (GMDS)

[since 2024]
Member of the working group for public relations (AG Öffentlichkeitsarbeit) of the IBS-DR

[2021 - 2025]
Co-Speaker of „Early Career Working Group (AG Nachwuchs) of the IBS-DR

[since 2019]
Member of the working group on population genetics (AG Pupulationsgenetik) of the IBS-DR

[since 2019]
Member of „Early Career Working Group (AG Nachwuchs) of the IBS-DR

[since 2018]
Member of the German region of the International Biometric Society (IBS-DR)

[since 2018]
Member of the „International Genetic Epidemiology Society“ (IGES)

Awards

[2024]
Young Teaching Award (Section Medicine), University of Lübeck 

[2022]
Science Award (Section Medicine), University of Lübeck

Selected Publications

  1. Laabs B-H, Lohmann K, Vollstedt EJ, Reinberger T, Nuxoll LM, Kilic-Berkmen G, Perlmutter JS, Loens S, Cruchaga C, Franke A, Dobricic V, Hinrichs F, Grözinger A, Altenmüller E, Bellows S, Boesch S, Bressman SB, Duque KR, Espay AJ, Ferbert A, Feuerstein JS, Frank S, Gasser T, Haslinger B, Jech R, Kaiser F, Kamm C, Kollewe K, Kühn AA, LeDoux MS, Lohmann E, Mahajan A, Münchau A, Multhaupt-Buell T, Pantelyat A, Pirio Richardson SE, Raymond D, Reich SG, Saunders Pullman R, Schormair B, Sharma N, Sichani AH, Simonyan K, Volkmann J, Wagle Shukla A, Winkelmann J, Wright LJ, Zech M, Zeuner KE, Zittel S, Kasten M, Sun YV, Bäumer T, Brüggemann N, Ozelius LJ, Jinnah HA, Klein C, König IR (2024) Genetic Risk Factors in Isolated Dystonia Escape Genome-Wide Association Studies. Mov Disord 39: 2110-2116. doi: 10.1002/mds.29968 OA
  2. Laabs B-H, Kronziel LL, König IR, Szymczak S (2024) Construction of Artificial Most Representative Trees by Minimizing Tree-Based Distance Measures. In: Longo, L., Lapuschkin, S., Seifert, C. (eds) Explainable Artificial Intelligence. xAI 2024. Communications in Computer and Information Science, vol 2154. Springer, Cham. doi: 10.1007/978-3-031-63797-1_15
  3. Szepannek G & von Holt B-H (2024) Can’t see the forest for the trees. Behaviormetrika 51:411-423. doi: 10.1007/s41237-023-00205-2 OA
  4. Laabs B-H, Westenberger A & König IR (2023) Identification of representative trees in random forests based on a new tree-based distance measure. Adv Data Anal Classif 18:363-380. doi: 10.1007/s11634-023-00537-7. OA
  5. Steinhardt J, Hanssen H, Heldmann M, Sprenger A, Laabs B-H, Domingo A, Reyes CJ, Prasuhn J, Brand M, Rosales RL, Münte TF, Klein C, Westenberger A, Oropilla JQ, Diesta CCE & Brüggemann N. Prodromal X-Linked Dystonia-Parkinsonism is Characterized by a Subclinical Motor Phenotype. Mov Disord 2022;37:1474-1482. doi: 10.1002/mds.29033. OA
  6. Koch S, Laabs B-H, Kasten M, Vollstedt E-J, Becktepe JS, Brüggemann N, Franke A, Krämer U, Kuhlenbäumer G, Lieb W, Mollenhauer B, Neis M, Trenkwalder C, Schaeffer E, Usnich T, Wittig M, Klein C, König IR, Lohmann K, Krawczak M & Caliebe A. Validity and Prognostic Value of a Polygenic Risk Score for Parkinson’s Disease. Genes 2021;12:1859. doi: 10.3390/genes12121859. OA
  7. Balck A, Schaake S, Kuhnke NS, Domingo A, Madoev H, Margolesky J, Dobricic V, Alvarez-Fischer D, Laabs B-H, Kasten M, Lou W, Nicolas G, Marras C, Lohmann K, Klein C & Westenberger A. Genotype-phenotype relations in primary familial brain calcification: Systematic MDSGene review. Mov Disord 2021;36:2468-2480. doi: 10.1002/mds.28753. OA
  8. Reyes CJ, Laabs B-H, Schaake S, Lüth T, Ardicoglu R, Rakovic A, Grütz K, Alvarez-Fischer D, Jamora RDG, Rosales RL, Weyers I, König IR, Brüggemann N, Klein C, Dobricic V, Westenberger A & Trinh J. Brain regional differences in hexanucleotide repeat length in X-linked dystonia-parkinsonism using nanopore sequencing. Neurol Genet 2021;7:1. doi: 10.1212/NXG.0000000000000608. OA
  9. Laabs B-H, Klein C, Pozojevic J, Domingo A, Brüggemann N, Grütz K, Rosales RL, Jamora RD, Saranza G, Diesta CCE, Wittig M, Schaake S, Dulovic-Mahlow M, Quismundo J, Otto P, Acuna P, Go C, Sharma N, Multhaupt-Buell T, Müller U, Hanssen H, Kilpert F, Franke A, Rolfs A, Bauer P, Dobricic V, Lohmann K, Ozelius LJ, Kaiser FJ, König IR & Westenberger A. Identifying genetic modifiers of age-associated penetrance in X-linked dystonia-parkinsonism. Nat Commun 2021;12:3216. doi: 10.1038/s41467-021-23491-4. OA
  10. Westenberger A, Reyes CJ, Saranza G, Dobricic V, Hanssen H, Domingo A, Laabs B-H, Schaake S, Pozojevic J, Rakovic A, Grütz K, Begemann K, Walter U, Dressler D, Bauer P, Rolfs A, Münchau A, Kaiser FJ, Ozelius LJ, Jamora RD, Rosales RL, Diesta CCE, Lohmann K, König IR, Brüggemann N & Klein C. A hexanucleotide repeat modifies expressivity of X-linked dystonia parkinsonism. Ann Neurol 2019;85:812-822. doi: 10.1002/ana.25488.

Supervised Theses

  • Masterarbeit (Universität zu Lübeck, ongoing): Quantification of uncertainty based on missing data in prediction models
  • Masterarbeit (Universität zu Lübeck, 2025): Use of variable selection when creating representative trees for random forests
  • Masterarbeit (Universität zu Lübeck, 2024): Usage of oblique splits in artificial representative trees for random forests
  • Masterarbeit (Universität zu Lübeck, 2023): Generation of ensembles of most representative trees using clustering
  • Bachelorarbeit (Universität zu Lübeck, 2023): Optimizing the prediction accuracy of random forests by distance-based elimination of outliers

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