Work

Publisher Correction: Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence

Year: 2026

Type: erratum

Abstract: The original version of this article contained typographical errors in the axis labels of Figure 2b, Figure 2e, and Figure 3b. The original article has been corrected.

Source: npj Digital Medicine

DOI: 10.1038/s41746-026-02833-w

Authors: Maximilian Ferle, Jonas Ader, Thomas Wiemers, Nora Grieb, Beatrice Berneck, Adrian Lindenmeyer, Hartmut Goldschmidt, Elias K. Mai, Uta Bertsch, Hans-Jonas Meyer, Thomas Neumuth, Markus Kreuz, Kristin Reiche, Maximilian Merz

Institutions: University Hospital Leipzig, Fraunhofer Institute for Cell Therapy and Immunology, Center for Scalable Data Analytics and Artificial Intelligence, Leipzig University, Heidelberg University, University Hospital Heidelberg, National Center for Tumor Diseases, Memorial Sloan Kettering Cancer Center

Language: English

Topic: Explainable Artificial Intelligence (XAI)

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,090

OpenAlex ID: W7164944934

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