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Dietrich Rebholz-Schuhmann

Dietrich Rebholz-Schuhmann

D-Index & Metrics

Computer Science

D-Index
42
Citations
5669
World Ranking
8524
National Ranking
420

Overview

Dietrich Rebholz-Schuhmann is affiliated with the University of Cologne in Germany. Their research spans multiple fields, with a focus on biochemistry, genetics, molecular biology, and computer science. The subfields of study prominently include molecular biology, artificial intelligence, information systems, information systems and management, and health informatics.

Their work prominently addresses several main topics, notably:

  • Bioinformatics and Genomic Networks
  • Biomedical Text Mining and Ontologies
  • Research Data Management Practices
  • Scientific Computing and Data Management
  • Semantic Web and Ontologies
  • Explainable Artificial Intelligence (XAI)
  • Artificial Intelligence in Healthcare and Education

Dietrich Rebholz-Schuhmann has co-authored publications with several frequent collaborators, including:

  • Leyla Jael Castro
  • Stefan Decker
  • Oya Beyan
  • Olga Giraldo
  • Michael Cochez

A significant portion of their research output has been published in various venues, where they have multiple contributions. These venues include:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • Proceedings of the Conference on Research Data Infrastructure
  • IEEE Access
  • Briefings in Bioinformatics

The scientist's recent papers demonstrate an interest in explainable artificial intelligence applied to bioinformatics and healthcare challenges. Notable publications include:

  • Explainable AI for Bioinformatics: Methods, Tools and Applications, 2023, Briefings in Bioinformatics
  • DeepKneeExplainer: Explainable Knee Osteoarthritis Diagnosis From Radiographs and Magnetic Resonance Imaging, 2021, IEEE Access
  • DeepCOVIDExplainer: Explainable COVID-19 Diagnosis Based on Chest X-ray Images, 2020, arXiv (Cornell University)
  • Adversary-Aware Multimodal Neural Networks for Cancer Susceptibility Prediction From Multiomics Data, 2022, IEEE Access
  • Explainable AI for Bioinformatics: Methods, Tools, and Applications, 2022, arXiv (Cornell University)

Best Publications

  • Text processing through Web services

    Dietrich Rebholz-Schuhmann;Miguel Arregui;Sylvain Gaudan;Harald Kirsch

  • Text-mining solutions for biomedical research: enabling integrative biology.

    Dietrich Rebholz-Schuhmann;Anika Oellrich;Robert Hoehndorf

  • Deep learning-based clustering approaches for bioinformatics

    Md. Rezaul Karim;Oya Beyan;Oya Beyan;Achille Zappa;Ivan G. Costa

  • EBIMed---text crunching to gather facts for proteins from Medline

    Dietrich Rebholz-Schuhmann;Harald Kirsch;Miguel Arregui;Sylvain Gaudan

  • Facts from text--is text mining ready to deliver?

    Dietrich Rebholz-Schuhmann;Harald Kirsch;Francisco Couto

  • Automatic recognition of conceptualization zones in scientific articles and two life science applications

    Maria Liakata;Shyamasree Saha;Simon Dobnik;Colin Batchelor

  • Assessment of disease named entity recognition on a corpus of annotated sentences

    Antonio Jimeno;Ernesto Jimenez-Ruiz;Vivian Lee;Sylvain Gaudan

  • Text mining for biology - the way forward: opinions from leading scientists

    Russ B. Altman;Casey M. Bergman;Judith A. Blake;Christian Blaschke

  • Resolving abbreviations to their senses in Medline

    S. Gaudan;H. Kirsch;D. Rebholz-Schuhmann

  • CALBC silver standard corpus.

    Dietrich Rebholz-Schuhmann;Antonio José Jimeno Yepes;Erik M Van Mulligen;Ning Kang

  • DeepCOVIDExplainer: Explainable COVID-19 Diagnosis from Chest X-ray Images

    Md. Rezaul Karim;Till Dohmen;Michael Cochez;Oya Beyan

  • MeSH Up

    Dolf Trieschnigg;Piotr Pezik;Vivian Lee;Franciska de Jong

  • Using argumentation to extract key sentences from biomedical abstracts.

    Patrick Ruch;Celia Boyer;Christine Chichester;Imad Tbahriti;Imad Tbahriti

  • Biological network extraction from scientific literature: state of the art and challenges

    Chen Li;Maria Liakata;Maria Liakata;Dietrich Rebholz-Schuhmann;Dietrich Rebholz-Schuhmann

  • Automatic extraction of mutations from Medline and cross‐validation with OMIM

    Dietrich Rebholz‐Schuhmann;Stephane Marcel;Sylvie Albert;Ralf Tolle

  • Ontology refinement for improved information retrieval

    Antonio Jimeno-Yepes;Rafael Berlanga-Llavori;Dietrich Rebholz-Schuhmann

  • GOAnnotator: linking protein GO annotations to evidence text

    Francisco M Couto;Mário J Silva;Vivian Lee;Emily Dimmer

  • Gene Regulation Ontology (GRO): Design Principles and Use Cases

    Elena Beisswanger;Vivian Lee;Jung-Jae Kim;Dietrich Rebholz-Schuhmann

  • Integrating protein-protein interactions and text mining for protein function prediction.

    Samira Jaeger;Samira Jaeger;Sylvain Gaudan;Ulf Leser;Dietrich Rebholz-Schuhmann

  • Relations as patterns: bridging the gap between OBO and OWL

    Robert Hoehndorf;Anika Oellrich;Michel Dumontier;Janet Kelso

  • Assessment of NER solutions against the first and second CALBC Silver Standard Corpus.

    Dietrich Rebholz-Schuhmann;Antonio Jimeno Yepes;Chen Li;Şenay Kafkas

  • DeepCOVIDExplainer: Explainable COVID-19 Predictions Based on Chest X-ray Images

    Md. Rezaul Karim;Till Döhmen;Dietrich Rebholz-Schuhmann;Stefan Decker

Frequent Co-Authors

Robert Hoehndorf
Robert Hoehndorf King Abdullah University of Science and Technology
Udo Hahn
Udo Hahn Friedrich Schiller University Jena
Erik M. van Mulligen
Erik M. van Mulligen Erasmus University Rotterdam
Nigel Collier
Nigel Collier University of Cambridge
Ernesto Jiménez-Ruiz
Ernesto Jiménez-Ruiz City, University of London
Georgios V. Gkoutos
Georgios V. Gkoutos University of Birmingham
Maria Liakata
Maria Liakata Queen Mary University of London
Francisco M. Couto
Francisco M. Couto University of Lisbon
Sampo Pyysalo
Sampo Pyysalo University of Turku
Axel-Cyrille Ngonga Ngomo
Axel-Cyrille Ngonga Ngomo University of Paderborn

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