REVIEW
Accepted on 29 Aug 2025
Artificial Intelligence Integrates Multi-Omics Data for Precision Stratification and Drug Resistance Prediction in Breast Cancer
doi 10.3389/fonc.2025.1612474
- Frontiers in Oncology
- Breast Cancer
- Research Topics
- AI-Powered Insights: Predicting Treatment Response and Prognosis in Breast Cancer
AI-Powered Insights: Predicting Treatment Response and Prognosis in Breast Cancer
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Articles
ORIGINAL RESEARCH
Accepted on 12 Aug 2025
Construction of a Prediction Model for Axillary Lymph Node Metastasis in Breast Cancer Patients Based on a Multimodal Fusion Strategy of Ultrasound and Pathological Images
doi 10.3389/fonc.2025.1591858
- 158 views
ORIGINAL RESEARCH
Published on 17 Jul 2025
Integrating single-cell regulatory atlas and multi-omics data for differential treatment response and multimodal predictive modeling in CDK 4/6 inhibitor-treated breast cancer
doi 10.3389/fonc.2025.1585574
- 1,191 views
CASE REPORT
Published on 19 Jun 2025
Multiple drug resistance caused by germline mutation of exon 27 of BRCA2 gene in triple-negative breast cancer: a case report and literature review
doi 10.3389/fonc.2025.1602870
- 911 views
- 1 citation
ORIGINAL RESEARCH
Published on 11 Jun 2025
AI-augmented pathology: the experience of transfer learning and intra-domain data diversity in breast cancer metastasis detection
doi 10.3389/fonc.2025.1598289
- 978 views
ORIGINAL RESEARCH
Published on 27 May 2025
Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine
doi 10.3389/fimmu.2025.1581982
- 2,089 views
ORIGINAL RESEARCH
Published on 21 May 2025
External validation of the Oncotype DX breast cancer recurrence score nomogram and development and validation of a novel machine learning-based model to predict postoperative overall survival and guide adjuvant chemotherapy in ER positive, Her-2 negative breast cancer patients: a retrospective cohort study
doi 10.3389/fonc.2025.1586262
- 1,213 views
ORIGINAL RESEARCH
Published on 14 May 2025
Comparative analysis of multi-zone peritumoral radiomics in breast cancer for predicting NAC response using ABVS-based deep learning models
doi 10.3389/fonc.2025.1586715
- 1,160 views
Published in
Frontiers in Oncology
Breast Cancer
Participating Journals
Frontiers in Endocrinology
- 4.6 impact factor
- 7.4 citescore
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