
The use of biomarkers in breast cancer has significantly improved patient outcomes through targeted therapies, such as hormone therapy anti-Her2 therapy and CDK4/6 or PARP inhibitors. However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors. The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers. This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification. We examined the primary challenges and opportunities of these multimodal data integration algorithms, including their advantages, limitations, and critical considerations for future research. We aimed to describe models that are not only academically and preclinically relevant, but also applicable to clinical settings.
Mama - Càncer - Prognosi, CHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, Tumor, Otros calificadores::Otros calificadores::Otros calificadores::/farmacoterapia, COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumorales, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Prognosis::Neoplasm Staging, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::pronóstico::estadificación de neoplasias, Breast Neoplasms, Multimodal Imaging, Machine learning, Multimodal data integration, Biomarkers, Tumor, Humans, Article(s) from the Special Issue on: Translational Oncology; Edited by Dr. Serena Di Cosimo, RC254-282, Mama - Càncer - Imatgeria, Neoplasm Staging, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Multimodal Imaging, Multi-omics, Other subheadings::Other subheadings::Other subheadings::/drug therapy, Marcadors tumorals, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Deep learning, Prognosis, Mama - Càncer - Tractament, Data integration, Female, Stratification, ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias de la mama, DISEASES::Neoplasms::Neoplasms by Site::Breast Neoplasms, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::imagen multimodal, Algorithms
Mama - Càncer - Prognosi, CHEMICALS AND DRUGS::Biological Factors::Biomarkers::Biomarkers, Tumor, Otros calificadores::Otros calificadores::Otros calificadores::/farmacoterapia, COMPUESTOS QUÍMICOS Y DROGAS::factores biológicos::biomarcadores::marcadores tumorales, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Prognosis::Neoplasm Staging, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::pronóstico::estadificación de neoplasias, Breast Neoplasms, Multimodal Imaging, Machine learning, Multimodal data integration, Biomarkers, Tumor, Humans, Article(s) from the Special Issue on: Translational Oncology; Edited by Dr. Serena Di Cosimo, RC254-282, Mama - Càncer - Imatgeria, Neoplasm Staging, ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Multimodal Imaging, Multi-omics, Other subheadings::Other subheadings::Other subheadings::/drug therapy, Marcadors tumorals, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, Deep learning, Prognosis, Mama - Càncer - Tractament, Data integration, Female, Stratification, ENFERMEDADES::neoplasias::neoplasias por localización::neoplasias de la mama, DISEASES::Neoplasms::Neoplasms by Site::Breast Neoplasms, TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::imagen multimodal, Algorithms
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| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
