ArticleFrontiers in oncology2021
Robust Prognostic Subtyping of Muscle-Invasive Bladder Cancer Revealed by Deep Learning-Based Multi-Omics Data Integration.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 22 citations in OpenAlex.
- Artificial intelligence in genitourinary pathology.Histopathology · 2026Review
- Urine-derived induced pluripotent stem cells for non-invasive diagnosis of bladder cancer.Journal of Cancer · 2026Review
- Adaptive multi-omics integration framework for breast cancer survival analysis.Scientific reports · 2025Article
- Article
- Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification.Discover oncology · 2025Review
- Review
- Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.Nature communications · 2024Article
- Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.Current medicinal chemistry · 2024Review
- A deep learning approach based on multi-omics data integration to construct a risk stratification prediction model for skin cutaneous melanoma.Journal of cancer research and clinical oncology · 2023Article
- Deep Learning Techniques with Genomic Data in Cancer Prognosis: A Comprehensive Review of the 2021-2023 Literature.Biology · 2023Article
- The long non-coding RNA keratin-7 antisense acts as a new tumor suppressor to inhibit tumorigenesis and enhance apoptosis in lung and breast cancers.Cell death & disease · 2023Article
- Deep learning facilitates multi-data type analysis and predictive biomarker discovery in cancer precision medicine.Computational and structural biotechnology journal · 2023Review
- Combining Molecular, Imaging, and Clinical Data Analysis for Predicting Cancer Prognosis.Cancers · 2022Review
- Multimodal deep learning for biomedical data fusion: a review.Briefings in bioinformatics · 2022Review
- Angiogenesis goes computational - The future way forward to discover new angiogenic targets?Computational and structural biotechnology journal · 2022Review
- Machine Learning: A New Prospect in Multi-Omics Data Analysis of Cancer.Frontiers in genetics · 2022Review
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Muscle-invasive bladder cancer (MIBC) is the most common urinary system carcinoma associated with poor outcomes. It is necessary to develop a robust classification system for prognostic prediction of MIBC. Recently, increasing omics data at different levels of MIBC were produced, but few integration methods were used to classify MIBC that reflects the patient's prognosis. In this study, we constructed an autoencoder based deep learning framework to integrate multi-omics data of MIBC and clustered samples into two different subgroups with significant overall survival difference (
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