Explainable Artificial Intelligence Reveals Novel Insight into Tumor Microenvironment Conditions Linked with Better Prognosis in Patients with Breast Cancer
出版年份 2021 全文链接
标题
Explainable Artificial Intelligence Reveals Novel Insight into Tumor Microenvironment Conditions Linked with Better Prognosis in Patients with Breast Cancer
作者
关键词
-
出版物
Cancers
Volume 13, Issue 14, Pages 3450
出版商
MDPI AG
发表日期
2021-07-09
DOI
10.3390/cancers13143450
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Tumor-Associated Macrophages: Recent Insights and Therapies
- (2020) Jiawei Zhou et al. Frontiers in Oncology
- Explainable AI meets persuasiveness: Translating reasoning results into behavioral change advice
- (2020) Mauro Dragoni et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- Revisiting the role of CD4+ T cells in cancer immunotherapy—new insights into old paradigms
- (2020) Rong En Tay et al. CANCER GENE THERAPY
- Complement Signals Determine Opposite Effects of B Cells in Chemotherapy-Induced Immunity
- (2020) Yiwen Lu et al. CELL
- Multi-panel immunofluorescence analysis of tumor infiltrating lymphocytes in triple negative breast cancer: Evolution of tumor immune profiles and patient prognosis
- (2020) Ting-Fang He et al. PLoS One
- A case-based ensemble learning system for explainable breast cancer recurrence prediction
- (2020) Dongxiao Gu et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- Predicted Prognosis of Pancreatic Cancer Patients by Machine Learning—Letter
- (2020) Julius M. Kernbach et al. CLINICAL CANCER RESEARCH
- Next-Generation Analytics for Omics Data
- (2020) Jun Li et al. CANCER CELL
- Tumor Endothelial Cells (TECs) as Potential Immune Directors of the Tumor Microenvironment – New Findings and Future Perspectives
- (2020) Laurenz Nagl et al. Frontiers in Cell and Developmental Biology
- Radiomic Analysis in Contrast-Enhanced Spectral Mammography for Predicting Breast Cancer Histological Outcome
- (2020) Daniele La Forgia et al. Diagnostics
- Machine Learning Algorithms to Predict Recurrence within 10 Years after Breast Cancer Surgery: A Prospective Cohort Study
- (2020) Shi-Jer Lou et al. Cancers
- A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
- (2020) Erico Tjoa et al. IEEE Transactions on Neural Networks and Learning Systems
- Explainable artificial intelligence for breast cancer: a visual case-based reasoning approach
- (2019) Jean-Baptiste Lamy et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- Breast Cancer Prognosis Using a Machine Learning Approach
- (2019) Patrizia Ferroni et al. Cancers
- Infiltration of CD8+ T cells into tumor cell clusters in triple-negative breast cancer
- (2019) Xuefei Li et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action
- (2019) Jason H. Yang et al. CELL
- Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers
- (2019) Eiryo Kawakami et al. CLINICAL CANCER RESEARCH
- Breast MRI background parenchymal enhancement as an imaging bridge to molecular cancer sub-type
- (2019) Giuseppe Dilorenzo et al. EUROPEAN JOURNAL OF RADIOLOGY
- Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology
- (2019) Gregor Sturm et al. BIOINFORMATICS
- Chimeric antigen receptor macrophage therapy for breast tumours mediated by targeting the tumour extracellular matrix
- (2019) Wenlong Zhang et al. BRITISH JOURNAL OF CANCER
- Cancer-associated fibroblasts: an emerging target of anti-cancer immunotherapy
- (2019) Tongyan Liu et al. Journal of Hematology & Oncology
- The Missing Pieces of Artificial Intelligence in Medicine
- (2019) Coryandar Gilvary et al. TRENDS IN PHARMACOLOGICAL SCIENCES
- B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer
- (2019) Daniel P. Hollern et al. CELL
- Unraveling triple-negative breast cancer tumor microenvironment heterogeneity: towards an optimized treatment approach
- (2019) Yacine Bareche et al. JNCI-Journal of the National Cancer Institute
- A review of statistical and machine learning methods for modeling cancer risk using structured clinical data
- (2018) Aaron N. Richter et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- The Cancer Genome Atlas: Creating Lasting Value beyond Its Data
- (2018) Carolyn Hutter et al. CELL
- Next-Generation Machine Learning for Biological Networks
- (2018) Diogo M. Camacho et al. CELL
- New Insights into Tumor-Infiltrating B Lymphocytes in Breast Cancer: Clinical Impacts and Regulatory Mechanisms
- (2018) Meng Shen et al. Frontiers in Immunology
- Activation and Regulation of B Cell Responses by Invariant Natural Killer T Cells
- (2018) Derek G. Doherty et al. Frontiers in Immunology
- Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
- (2018) Freddie Bray et al. CA-A CANCER JOURNAL FOR CLINICIANS
- Endoscopic Diagnostic Support System for cT1b Colorectal Cancer Using Deep Learning
- (2018) Nao Ito et al. ONCOLOGY
- Classification of triple-negative breast cancers based on Immunogenomic profiling
- (2018) Yin He et al. JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH
- Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data
- (2017) Julien Racle et al. eLife
- Triple-negative breast cancer: challenges and opportunities of a heterogeneous disease
- (2016) Giampaolo Bianchini et al. Nature Reviews Clinical Oncology
- Cancer-associated fibroblast-secreted CXCL16 attracts monocytes to promote stroma activation in triple-negative breast cancers
- (2016) Roni Allaoui et al. Nature Communications
- Does an NKT-cell-based immunotherapeutic approach have a future in multiple myeloma?
- (2016) Mérédis Favreau et al. Oncotarget
- B cell regulation of the anti-tumor response and role in carcinogenesis
- (2016) Marc Schwartz et al. Journal for ImmunoTherapy of Cancer
- Interaction between tumour-infiltrating B cells and T cells controls the progression of hepatocellular carcinoma
- (2015) Marta Garnelo et al. GUT
- Robust enumeration of cell subsets from tissue expression profiles
- (2015) Aaron M Newman et al. NATURE METHODS
- CD4+ and CD8+ T cells have opposing roles in breast cancer progression and outcome
- (2015) Yi Huang et al. Oncotarget
- Natural killer T cell activation overcomes immunosuppression to enhance clearance of postsurgical breast cancer metastasis in mice
- (2015) Simon Gebremeskel et al. OncoImmunology
- Machine learning applications in cancer prognosis and prediction
- (2015) Konstantina Kourou et al. Computational and Structural Biotechnology Journal
- B cells and their mediators as targets for therapy in solid tumors
- (2013) Andrew J. Gunderson et al. EXPERIMENTAL CELL RESEARCH
- Spatiotemporal Dynamics of Intratumoral Immune Cells Reveal the Immune Landscape in Human Cancer
- (2013) Gabriela Bindea et al. IMMUNITY
- The role of tumor-associated macrophages in breast cancer progression
- (2013) ELIAS OBEID et al. INTERNATIONAL JOURNAL OF ONCOLOGY
- Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
- (2013) J. Gao et al. Science Signaling
- The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data: Figure 1.
- (2012) Ethan Cerami et al. Cancer Discovery
- Activated NKT Cells and NK Cells Render T Cells Resistant to Myeloid-Derived Suppressor Cells and Result in an Effective Adoptive Cellular Therapy against Breast Cancer in the FVBN202 Transgenic Mouse
- (2011) M. Kmieciak et al. JOURNAL OF IMMUNOLOGY
- Combinatorial biomarker expression in breast cancer
- (2010) Emad A. Rakha et al. BREAST CANCER RESEARCH AND TREATMENT
- Response to Neoadjuvant Therapy and Long-Term Survival in Patients With Triple-Negative Breast Cancer
- (2008) Cornelia Liedtke et al. JOURNAL OF CLINICAL ONCOLOGY
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