Towards precision oncology: a multi-level cancer classification system integrating liquid biopsy and machine learning

The identified biomarkers enhance the interpretability of the diagnosis, facilitating more informed decision-making. The system's performance underscores its effectiveness in tissue localization, contributing to improved patient outcomes through timely medical interventions.

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Publication Details

Journal
BioData Mining
Published
2025-04-11
DOI
https://doi.org/10.1186/s13040-025-00439-8
Citations
5
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
4.68

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article

Towards precision oncology: a multi-level cancer classification system integrating liquid biopsy and machine learning

Sara El-Metwally, Taher Hamza, Amr Eledkawy
5 citations
BioData Mining
Cancer Genomics and Diagnostics
4.68
article

Towards precision oncology: a multi-level cancer classification system integrating liquid biopsy and machine learning

Sara El-Metwally, Taher Hamza, Amr Eledkawy
article en
5 citations

Abstract

The identified biomarkers enhance the interpretability of the diagnosis, facilitating more informed decision-making. The system's performance underscores its effectiveness in tissue localization, contributing to improved patient outcomes through timely medical interventions.

BioData MiningVol. 18(1)
Mansoura University (EG)
Science and Technology Development Fund
Openalex Percentile: Top 5%
Cancer Genomics and Diagnostics
4.68
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