Medizinische Universität Graz - Research portal
Angerschmid Alessa |
** = Publications listed in SCI/SSCI/Pubmed
2024
Full paper/article (Journal)
** Metsch, JM; Saranti, A; Angerschmid, A; Pfeifer, B; Klemt, V; Holzinger, A; Hauschild, AC
CLARUS: An interactive explainable AI platform for manual counterfactuals in graph neural networks.
J Biomed Inform. 2024; 150:104600
Doi: 10.1016/j.jbi.2024.104600
Web of Science
PubMed
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FullText_MUG
** Retzlaff, CO; Angerschmid, A; Saranti, A; Schneeberger, D; Röttger, R; Müller, H; Holzinger, A
Post-hoc vs ante-hoc explanations: xAI design guidelines for data scientists
COGN SYST RES. 2024; 86: 101243
Doi: 10.1016/j.cogsys.2024.101243
Web of Science
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2023
Review
** Holzinger, A; Saranti, A; Angerschmid, A; Finzel, B; Schmid, U; Mueller, H
Toward human-level concept learning: Pattern benchmarking for AI algorithms.
Patterns (N Y). 2023; 4(8): 100788
Doi: 10.1016/j.patter.2023.100788
[OPEN ACCESS]
Web of Science
PubMed
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Correction
** Finzel, B; Saranti, A; Angerschmid, A; Tafler, D; Pfeifer, B; Holzinger, A
Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs (vol 36, pg 271, 2022)
KUNSTL INTELL. 2023;
Doi: 10.1007/s13218-022-00789-z
Web of Science
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2022
Full paper/article (Journal)
** Angerschmid, A; Zhou, JL; Theuermann, K; Chen, F; Holzinger, A
Fairness and Explanation in AI-Informed Decision Making
MACH LEARN KNOW EXTR. 2022; 4(2): 556-579.
Doi: 10.3390/make4020026
Web of Science
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** Finzel, B; Saranti, A; Angerschmid, A; Tafler, D; Pfeifer, B; Holzinger, A
Generating Explanations for Conceptual Validation of Graph Neural Networks
KUNSTL INTELL. 2022;
Doi: 10.1007/s13218-022-00781-7
[OPEN ACCESS]
Web of Science
PubMed
FullText
FullText_MUG
** Saranti, A; Hudec, M; Mináriková, E; Takác̆, Z; Großschedl, U; Koch, C; Pfeifer, B; Angerschmid, A; Holzinger, A
Actionable Explainable AI (AxAI): A Practical Example with Aggregation Functions for Adaptive Classification and Textual Explanations for Interpretable Machine Learning.
Machine Learning and Knowledge Extraction. 2022; 4(4): 924-953.
Doi: 10.3390/make4040047
Web of Science
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