🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Tobias Seibel

RWTH Aachen University

ORCID: 0009-0004-9115-3228
MedicineImmunology and Microbiology

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile
0Author DataRank

Indexed papers

0in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 3 papers. Top paper: “Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study”.

Direct prediction of Homologous Recombination Deficiency from routine histology in ten different tumor types with attention-based Multiple Instance Learning: a development and validation study

medRxiv(2023)10.1101/2023.03.08.23286975
N/A
0DataRank · unranked
13 citations

Omar S. M. El Nahhas, Hannah Sophie Muti, Tobias Seibel, Didem Çifçi, Marko van Treeck +10 more

Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease

Liver International(2025)10.1111/liv.70164
N/A
0DataRank · unranked
7 citations

Benjamin P. M. Laevens, Teresa Lemainque, Gustav Müller‐Franzes, Tobias Seibel, Carola Dlugosch +22 more

280P Machine learning for multi-omics risk prediction of cholangiocarcinoma in the general population

ESMO Real World Data and Digital Oncology(2025)10.1016/j.esmorw.2025.100476
N/A
0DataRank · unranked
0 citations

Jan Clusmann, P-H. Koop, Richardria Goodson, Tobias Seibel, Niharika Jakhar +12 more