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A Referencemodel for Explainable AI for the medical domain

Project Leader:

Holzinger Andreas

Duration:

04.11.2019-31.12.2022

Programme:

Einzelprojekt

Type of Research

basic research

Staff

Holzinger, Andreas, Project Leader

MUG Research Units

Institute for Medical Informatics, Statistics and Documentation

Funded by

FWF, Fonds zur Förderung der Wissenschaftlichen Forschung, Wien, Austria

FWF-Grant-DOI: 10.55776/P32554

Project results published

> Generating Explanations for Conceptual Validation ... KUNSTL INTELL. 2023;

> The augmented radiologist: artificial intelligence... Pediatr Radiol. 2022; 52(11):2074-2086

> Personas for Artificial Intelligence (AI) an Open ... IEEE ACCESS. 2022; 10: 23732-23747.

> Information fusion as an integrative cross-cutting... INFORM FUSION. 2022; 79: 263-278.

> Kandinsky Patterns... ARTIF INTELL. 2021; 300: 103546

> Toward Human-AI Interfaces to Support Explainabili... COMPUTER. 2021; 54(10): 78-86.

> The Ten Commandments of Ethical Medical AI... COMPUTER. 2021; 54(7): 119-123.

> Towards multi-modal causability with Graph Neural ... INFORM FUSION. 2021; 71: 28-37.

> AI and Big Data in Healthcare: Towards a More Comp... J CLIN MED. 2021; 10(4): 766

> Recommender systems in the healthcare domain: stat... J INTELL INF SYST. 2021;

> Classification by ordinal sums of conjunctive and ... KNOWL-BASED SYST. 2021; 220:

> KANDINSKY Patterns as IQ-Test for Machine Learning... In: Tjoa, AM editors(s). International Cross-Domain Conference for Machine Learning and Knowledge Extraction, Lecture Notes in Computer Science LNCS 11713. Cham: Springer/Nature; p. 1-14. 2019(ISBN: 978-3-030-29725-1)