Vol. 4 No. 2 (2024): Journal of Deep Learning in Genomic Data Analysis
Articles

Deep Learning-based Biomarker Discovery for Precision Oncology: Utilizing deep learning techniques to discover novel biomarkers for precision oncology, enabling targeted therapies and personalized treatment plans for cancer patients

Dr. Maria Rodriguez
Associate Professor of Public Health Informatics, Universidad Central de Venezuela

Published 06-09-2024

Keywords

  • Deep learning,
  • biomarker discovery

How to Cite

[1]
Dr. Maria Rodriguez, “Deep Learning-based Biomarker Discovery for Precision Oncology: Utilizing deep learning techniques to discover novel biomarkers for precision oncology, enabling targeted therapies and personalized treatment plans for cancer patients”, Journal of Deep Learning in Genomic Data Analysis, vol. 4, no. 2, pp. 12–19, Sep. 2024, Accessed: Dec. 22, 2024. [Online]. Available: https://thelifescience.org/index.php/jdlgda/article/view/30

Abstract

Deep learning has emerged as a powerful tool in the field of oncology, offering new avenues for biomarker discovery that can revolutionize precision medicine. This paper explores the application of deep learning techniques for the discovery of novel biomarkers in oncology, with a focus on enabling personalized treatment plans for cancer patients. By analyzing large-scale genomics, transcriptomics, and proteomics data, deep learning models can identify subtle patterns and associations that may serve as biomarkers for specific cancer types or subtypes. This paper reviews the current state of deep learning-based biomarker discovery in oncology, discusses challenges and opportunities, and provides insights into future directions in this rapidly evolving field.

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