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Random optimization-based feature selection for breast cancer outcome prediction using fully connected neural networks on multi-omic data

Published Online: 2026-04-02

Authors

Tamrakar, Poi

Pathak, Ganesh R.
License Information

Text and Data Mining valid from 2026-04-02

Accepted Manuscript valid from 2026-04-02
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Article History

Received: 5 December 2025

Accepted: 23 March 2026

First Online: 2 April 2026

Declarations

:

: This study utilized the publicly available METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) dataset, which contains fully de-identified patient data. The METABRIC dataset was originally collected with ethical approval from the relevant institutional review boards and ethics committees. As the present study involved secondary analysis of anonymized data and did not include direct interaction with human participants, additional ethical approval was not required. Informed consent was obtained from all participants by the original investigators at the time of data collection for the METABRIC study. No new participants were recruited for this research.

: Not applicable. The study does not include any identifiable individual data, images, or personal information.

: The authors declare no competing interests.

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