Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication
Published 2023 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication
Authors
Keywords
-
Journal
BioData Mining
Volume 16, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2023-07-22
DOI
10.1186/s13040-023-00338-w
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Cytokines secreted by inflamed oral mucosa: implications for oral cancer progression
- (2023) Erika B. Danella et al. ONCOGENE
- Cancer statistics, 2022
- (2022) Rebecca L. Siegel et al. CA-A CANCER JOURNAL FOR CLINICIANS
- Identification and Validation of DEPDC1B as an Independent Early Diagnostic and Prognostic Biomarker in Liver Hepatocellular Carcinoma
- (2022) Xiaoyan Fan et al. Frontiers in Genetics
- A Novel Deep Learning Method to Predict Lung Cancer Long-Term Survival With Biological Knowledge Incorporated Gene Expression Images and Clinical Data
- (2022) Shuo Wang et al. Frontiers in Genetics
- Artificial intelligence for multimodal data integration in oncology
- (2022) Jana Lipkova et al. CANCER CELL
- HiTIMED: hierarchical tumor immune microenvironment epigenetic deconvolution for accurate cell type resolution in the tumor microenvironment using tumor-type-specific DNA methylation data
- (2022) Ze Zhang et al. Journal of Translational Medicine
- Data-efficient and weakly supervised computational pathology on whole-slide images
- (2021) Ming Y. Lu et al. Nature Biomedical Engineering
- Regulated lytic cell death in breast cancer
- (2021) Mingcheng Liu et al. CELL BIOLOGY INTERNATIONAL
- A modified DeepWalk method for link prediction in attributed social network
- (2021) Kamal Berahmand et al. COMPUTING
- The remodelling of actin composition as a hallmark of cancer
- (2021) Rahul Suresh et al. Translational Oncology
- MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks
- (2021) Joshua J. Levy et al. npj Systems Biology and Applications
- Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
- (2021) Guang Yang et al. Information Fusion
- The Prognostic Implications of Tumor Infiltrating Lymphocytes in Colorectal Cancer: A Systematic Review and Meta-Analysis
- (2020) Gregory E. Idos et al. Scientific Reports
- Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations
- (2020) Zhi Huang et al. BMC Medical Genomics
- G2M Cell Cycle Pathway Score as a Prognostic Biomarker of Metastasis in Estrogen Receptor (ER)-Positive Breast Cancer
- (2020) Masanori Oshi et al. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
- Changes and prognostic values of tumor-infiltrating lymphocyte subsets after primary systemic therapy in breast cancer
- (2020) Soomin Ahn et al. PLoS One
- Autophagy and liver cancer
- (2020) Xiaojuan Chao et al. Clinical and Molecular Hepatology
- Explainability for artificial intelligence in healthcare: a multidisciplinary perspective
- (2020) Julia Amann et al. BMC Medical Informatics and Decision Making
- Deep learning-based cross-classifications reveal conserved spatial behaviors within tumor histological images
- (2020) Javad Noorbakhsh et al. Nature Communications
- The role of lysosomes in cancer development and progression
- (2020) Tao Tang et al. Cell and Bioscience
- Regulation of PD-L1 Expression by NF-κB in Cancer
- (2020) Fabrizio Antonangeli et al. Frontiers in Immunology
- Prognostic models for breast cancer: a systematic review
- (2019) Minh Tung Phung et al. BMC CANCER
- Deep learning with multimodal representation for pancancer prognosis prediction
- (2019) Anika Cheerla et al. BIOINFORMATICS
- Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning
- (2019) Sairam Tabibu et al. Scientific Reports
- Wnt/β-Catenin Signaling in Liver Cancers
- (2019) Wenhui Wang et al. Cancers
- The diverse roles of DNA methylation in mammalian development and disease
- (2019) Maxim V. C. Greenberg et al. NATURE REVIEWS MOLECULAR CELL BIOLOGY
- Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data
- (2019) Jie Hao et al. BMC Medical Genomics
- Semaphorin 5A suppresses the proliferation and migration of lung adenocarcinoma cells
- (2019) Pin‑Hao Ko et al. INTERNATIONAL JOURNAL OF ONCOLOGY
- Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
- (2018) Joel Saltz et al. Cell Reports
- Immune regulation of metastasis: mechanistic insights and therapeutic opportunities
- (2018) Olga S. Blomberg et al. Disease Models & Mechanisms
- Roads to melanoma: Key pathways and emerging players in melanoma progression and oncogenic signaling
- (2016) Jasmina Paluncic et al. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH
- TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data
- (2015) Antonio Colaprico et al. NUCLEIC ACIDS RESEARCH
- Machine learning: Trends, perspectives, and prospects
- (2015) M. I. Jordan et al. SCIENCE
- Involvement of the Androgen and Glucocorticoid Receptors in Bladder Cancer
- (2015) Lucien McBeth et al. International Journal of Endocrinology
- Machine learning applications in cancer prognosis and prediction
- (2015) Konstantina Kourou et al. Computational and Structural Biotechnology Journal
- Molecular Genetics of Clear-Cell Renal Cell Carcinoma
- (2014) James Brugarolas JOURNAL OF CLINICAL ONCOLOGY
- Upregulation of MAPK pathway is associated with survival in castrate-resistant prostate cancer
- (2011) R Mukherjee et al. BRITISH JOURNAL OF CANCER
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now