Computational Approaches in Breast Cancer Diagnosis and Prognosis
A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Physiology and Pathology".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 75
Special Issue Editors
Interests: bioinformatics; machine learning; artificial intelligence; evolutionary algorithm
Special Issue Information
Dear Colleagues,
Breast cancer remains one of the leading causes of cancer-related deaths worldwide, posing significant challenges in diagnosis, prognosis, and clinical decision-making. The complexity and heterogeneity of breast cancer-related data, which includes genomic, transcriptomic, clinical, and imaging datasets, further complicate their analysis and direct application in clinical settings. However, recent advancements in computational methodologies have revolutionized medical data analysis, presenting groundbreaking opportunities to enhance breast cancer diagnosis, prognosis, and treatment strategies.
This Special Issue aims to explore the application of advanced computational techniques in breast cancer prediction, early detection, biomarker discovery, and cancer progression modeling. We invite contributions that employ novel machine learning (ML), deep learning (DL), metaheuristic algorithms, network analysis, statistical modeling, and data fusion techniques across diverse breast cancer data, with the goal of improving diagnostic accuracy and prognosis.
Key topics include, but are not limited to:
- Development of computational models for breast cancer diagnosis and prognosis.
- Techniques for integrating and analyzing genomic, clinical, and imaging data.
- Advancements in ML and DL algorithms to enhance prediction accuracy.
- Identification and validation of biomarkers for early detection and prognosis.
This Special Issue serves as a platform to foster collaboration and advance computational methodologies in breast cancer research, ultimately improving patient outcomes and contributing to the future of personalized medicine.
Dr. Elham Pashaei
Dr. Jun Wan
Guest Editors
Manuscript Submission Information
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Keywords
- bioinformatics
- machine learning
- artificial intelligence
- breast cancer
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