ArticleCancers2021
Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
14 citing papers in PubMed, 30 citations in OpenAlex.
- AI-driven spatial mapping of myxoid stroma and tumor-infiltrating lymphocytes in esophageal squamous cell carcinoma.Esophagus : official journal of the Japan Esophageal Society · 2026Article
- Artificial intelligence-driven digital pathology in urological cancers: current trends and future directions.Prostate international · 2025Review
- Recent Advances in Artificial Intelligence for Precision Diagnosis and Treatment of Bladder Cancer: A Review.Annals of surgical oncology · 2025Review
- Computational Morphological Assessment of Bladder Cancer Tissue Is Prognostic of Recurrence and Overall Survival Following Transurethral Resection.JCO clinical cancer informatics · 2025Article
- Precise grading of non-muscle invasive bladder cancer with multi-scale pyramidal CNN.Scientific reports · 2024Article
- Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review.Cancers · 2023Review
- Article
- Multi-scale spatial modeling of immune cell distributions enables survival prediction in primary central nervous system lymphoma.iScience · 2023Article
- Recent Advancements in Deep Learning Using Whole Slide Imaging for Cancer Prognosis.Bioengineering (Basel, Switzerland) · 2023Review
- Proposal of an automated tumor-stromal ratio assessment algorithm and a nomogram for prognosis in early-stage invasive breast cancer.Cancer medicine · 2023Article
- Caveat Medicus: It's Time to Re-Think Stratification, You May Not Be Helping.Biomarker insights · 2023Article
- Radiomics for the Prediction of Overall Survival in Patients with Bladder Cancer Prior to Radical Cystectomy.Cancers · 2022Article
- A Novel Methodology for Measuring the Abstraction Capabilities of Image Recognition Algorithms.Journal of imaging · 2021Article
- Computational pathology in bladder cancer: A scoping review.Bladder cancer (Amsterdam, Netherlands)Review
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insight into patient prognosis. In this paper, we apply multiplex immunofluorescence to MIBC tissue sections to capture whole-slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1. We propose a machine-learning-based approach for the prediction of 5 year prognosis with different combinations of image, clinical, and spatial features. An ensemble model comprising several functionally different models successfully stratifies MIBC patients into two risk groups with high statistical significance (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.