Bladder Cancer

How artificial intelligence is transforming Bladder Cancer detection, diagnosis, and treatment.

101 Papers Open Access

Showing all 101 papers

Cited by 343
Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets

Med Phys, 2016

Open Access
Cited by 251
Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.

Sci Rep, 2017

Open Access
Cited by 235
Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.

Nat Commun, 2020

Open Access
Cited by 233
Augmented Bladder Tumor Detection Using Deep Learning

Eur Urol, 2019

Open Access
Cited by 182
Radiomics assessment of bladder cancer grade using texture features from diffusion-weighted imaging.

J Magn Reson Imaging, 2017

Open Access
Cited by 148
Support System of Cystoscopic Diagnosis for Bladder Cancer Based on Artificial Intelligence

J Endourol, 2020

Open Access
Cited by 143
Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework.

Front Endocrinol (Lausanne), 2023

Open Access
Cited by 140
Noninvasive diagnostic imaging using machine-learning analysis of nanoresolution images of cell surfaces: Detection of bladder cancer.

Proc Natl Acad Sci U S A, 2018

Open Access
Cited by 137
Open Radical Cystectomy versus Robot-Assisted Radical Cystectomy with Intracorporeal Urinary Diversion: Early Outcomes of a Single-Center Randomized Controlled Trial.

J Urol, 2022

Open Access
Cited by 133
Clinical and pathological implications of miRNA in bladder cancer.

Int J Nanomedicine, 2015

Open Access
Cited by 111
A urinary microRNA signature can predict the presence of bladder urothelial carcinoma in patients undergoing surveillance.

Br J Cancer, 2016

Open Access
Cited by 107
Machine learning models for predicting post-cystectomy recurrence and survival in bladder cancer patients.

PLoS One, 2019

Open Access
Cited by 106
Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.

Cancer Sci, 2021

Open Access
Cited by 94
The use of genetic programming in the analysis of quantitative gene expression profiles for identification of nodal status in bladder cancer.

BMC Cancer, 2006

Open Access
Cited by 87
Bladder cancer-associated gene expression signatures identified by profiling of exfoliated urothelia.

Cancer Epidemiol Biomarkers Prev, 2009

Open Access
Cited by 85
Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects.

World J Urol, 2020

Open Access
Cited by 83
Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement

Diagnostics (Basel), 2023

Open Access
Cited by 80
An Artificial Intelligence System for the Detection of Bladder Cancer via Cystoscopy: A Multicenter Diagnostic Study.

J Natl Cancer Inst, 2022

Open Access
Cited by 80
Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors.

Sci Rep, 2021

Open Access
Cited by 80
Role of genetic heterogeneity and epistasis in bladder cancer susceptibility and outcome: a learning classifier system approach.

J Am Med Inform Assoc, 2013

Open Access
Cited by 79
Multiresolution Application of Artificial Intelligence in Digital Pathology for Prediction of Positive Lymph Nodes From Primary Tumors in Bladder Cancer.

JCO Clin Cancer Inform, 2020

Open Access
Cited by 78
Identification of an immunotherapy-responsive molecular subtype of bladder cancer.

EBioMedicine, 2019

Open Access
Cited by 74
Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer.

Mol Med, 2022

Open Access
Cited by 73
Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

Tomography, 2019

Open Access
Cited by 73
Prediction of non-muscle invasive bladder cancer recurrence using machine learning of quantitative nuclear features.

Mod Pathol, 2022

Open Access
Cited by 72
Diagnostic Accuracy of CT for Prediction of Bladder Cancer Treatment Response with and without Computerized Decision Support.

Acad Radiol, 2019

Open Access
Cited by 72
Metabolite marker discovery for the detection of bladder cancer by comparative metabolomics.

Oncotarget, 2017

Open Access
Cited by 71
Deep Learning data integration for better risk stratification models of bladder cancer.

AMIA Jt Summits Transl Sci Proc, 2018

Open Access
Cited by 69
Histopathological distinction of non-invasive and invasive bladder cancers using machine learning approaches.

BMC Med Inform Decis Mak, 2020

Open Access
Cited by 67
APOBEC-mediated mutagenesis is a favorable predictor of prognosis and immunotherapy for bladder cancer patients: evidence from pan-cancer analysis and multiple databases.

Theranostics, 2022

Open Access
Cited by 67
The learning curve for robot-assisted radical cystectomy.

JSLS, 2009

Open Access
Cited by 64
Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.

Sci Rep, 2019

Open Access
Cited by 63
Impact of surgeon and volume on extended lymphadenectomy at the time of robot-assisted radical cystectomy: results from the International Robotic Cystectomy Consortium (IRCC).

BJU Int, 2013

Open Access
Cited by 62
Automated Extraction of Grade, Stage, and Quality Information From Transurethral Resection of Bladder Tumor Pathology Reports Using Natural Language Processing.

JCO Clin Cancer Inform, 2018

Open Access
Cited by 61
To construct a ceRNA regulatory network as prognostic biomarkers for bladder cancer.

J Cell Mol Med, 2020

Open Access
Cited by 60
Early oncologic outcomes of robotic vs. open radical cystectomy for urothelial cancer.

Urol Oncol, 2013

Open Access
Cited by 60
Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data.

Biomed Res Int, 2020

Open Access
Cited by 57
Deep learning diagnostics for bladder tumor identification and grade prediction using RGB method.

Sci Rep, 2022

Open Access
Cited by 55
Identification of Core Genes and Key Pathways via Integrated Analysis of Gene Expression and DNA Methylation Profiles in Bladder Cancer.

Med Sci Monit, 2018

Open Access
Cited by 55
Integrated analysis of a competing endogenous RNA network reveals key lncRNAs as potential prognostic biomarkers for human bladder cancer.

Medicine (Baltimore), 2018

Open Access
Cited by 54
Immune-related signature predicts the prognosis and immunotherapy benefit in bladder cancer.

Cancer Med, 2020

Open Access
Cited by 54
Predictive models of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer using nuclear morphology and tissue architecture.

Cell Rep Med, 2021

Open Access
Cited by 54
Transcriptome profiling of a multiple recurrent muscle-invasive urothelial carcinoma of the bladder by deep sequencing.

PLoS One, 2014

Open Access
Cited by 53
Accurate Diagnosis and Survival Prediction of Bladder Cancer Using Deep Learning on Histological Slides.

Cancers (Basel), 2022

Open Access
Cited by 53
Deep Learning on Enhanced CT Images Can Predict the Muscular Invasiveness of Bladder Cancer.

Front Oncol, 2021

Open Access
Cited by 53
Machine Learning in Prediction of Bladder Cancer on Clinical Laboratory Data.

Diagnostics (Basel), 2022

Open Access
Cited by 52
Using deep learning to identify bladder cancers with FGFR-activating mutations from histology images.

Cancer Med, 2021

Open Access
Cited by 50
On Urinary Bladder Cancer Diagnosis: Utilization of Deep Convolutional Generative Adversarial Networks for Data Augmentation

Biology (Basel), 2021

Open Access
Cited by 50
Study Progress of Radiomics With Machine Learning for Precision Medicine in Bladder Cancer Management.

Front Oncol, 2019

Open Access
Cited by 47
Impact of body mass index on robot-assisted radical cystectomy.

JSLS, 2008

Open Access
Cited by 46
Positive association between hypertension and urinary bladder cancer: epidemiologic evidence involving 79,236 propensity score-matched individuals.

Ups J Med Sci, 2018

Open Access
Cited by 45
Performing Automatic Identification and Staging of Urothelial Carcinoma in Bladder Cancer Patients Using a Hybrid Deep-Machine Learning Approach

Cancers (Basel), 2023

Open Access
Cited by 45
Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8+ T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study.

Int J Surg, 2024

Open Access
Cited by 44
Optimizing cystoscopy and TURBT: enhanced imaging and artificial intelligence.

Nat Rev Urol, 2025

Open Access
Cited by 43
Prediction of Prognosis and Recurrence of Bladder Cancer by ECM-Related Genes.

J Immunol Res, 2022

Open Access
Cited by 42
Predicting Recurrence of Non-Muscle-Invasive Bladder Cancer: Current Techniques and Future Trends.

Cancers (Basel), 2022

Open Access
Cited by 41
The Role of 18F-FDG PET/CT in Guiding Precision Medicine for Invasive Bladder Carcinoma.

Front Oncol, 2020

Open Access
Cited by 40
Bladder cancer prognosis using deep neural networks and histopathology images.

J Pathol Inform, 2022

Open Access
Cited by 40
Spatial heterogeneity and organization of tumor mutation burden with immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer.

J Pathol Inform, 2022

Open Access
Cited by 39
An artificial intelligence model for the pathological diagnosis of invasion depth and histologic grade in bladder cancer.

J Transl Med, 2023

Open Access
Cited by 39
CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.

Cancer Imaging, 2023

Open Access
Cited by 38
Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning.

Cancers (Basel), 2021

Open Access
Cited by 37
A panel of systemic inflammatory response biomarkers for outcome prediction in patients treated with radical cystectomy for urothelial carcinoma.

BJU Int, 2022

Open Access
Cited by 36
Artificial intelligence to improve cytology performance in urothelial carcinoma diagnosis: results from validation phase of the French, multicenter, prospective VISIOCYT1 trial.

World J Urol, 2023

Open Access
Cited by 35
Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.

PLoS One, 2013

Open Access
Cited by 35
Development of a Natural Language Processing Engine to Generate Bladder Cancer Pathology Data for Health Services Research.

Urology, 2017

Open Access
Cited by 34
A co-expression network for differentially expressed genes in bladder cancer and a risk score model for predicting survival.

Hereditas, 2019

Open Access
Cited by 34
Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

Front Immunol, 2021

Open Access
Cited by 34
Artificial intelligence application in the diagnosis and treatment of bladder cancer: advance, challenges, and opportunities.

Front Oncol, 2024

Open Access
Cited by 34
Identification of two-dimensional copper signatures in human blood for bladder cancer with machine learning.

Chem Sci, 2022

Open Access
Cited by 33
Artificial intelligence-driven consensus gene signatures for improving bladder cancer clinical outcomes identified by multi-center integration analysis.

Mol Oncol, 2022

Open Access
Cited by 33
Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features

Sci Rep, 2023

Open Access
Cited by 33
Predicting non-muscle invasive bladder cancer outcomes using artificial intelligence: a systematic review using APPRAISE-AI.

NPJ Digit Med, 2024

Open Access
Cited by 32
STAG2 loss-of-function affects short-range genomic contacts and modulates the basal-luminal transcriptional program of bladder cancer cells.

Nucleic Acids Res, 2021

Open Access
Cited by 31
A CT-based deep learning model predicts overall survival in patients with muscle invasive bladder cancer after radical cystectomy: a multicenter retrospective cohort study.

Int J Surg, 2024

Open Access
Cited by 31
Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review.

Cancers (Basel), 2023

Open Access
Cited by 31
Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center study.

Insights Imaging, 2024

Open Access
Cited by 29
Cell-free DNA Methylation as a Predictive Biomarker of Response to Neoadjuvant Chemotherapy for Patients with Muscle-invasive Bladder Cancer in SWOG S1314.

Eur Urol Oncol, 2023

Open Access
Cited by 29
Characterization of mRNA Expression and Endogenous RNA Profiles in Bladder Cancer Based on The Cancer Genome Atlas (TCGA) Database.

Med Sci Monit, 2019

Open Access
Cited by 29
Identification of immune-related genes as prognostic factors in bladder cancer.

Sci Rep, 2020

Open Access
Cited by 28
Deep learning in bladder cancer imaging: A review

Front Oncol, 2022

Open Access
Cited by 26
CT-based deep learning radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer.

Front Oncol, 2022

Open Access
Cited by 26
Online adaptive radiotherapy for bladder cancer using a simultaneous integrated boost and fiducial markers.

Radiat Oncol, 2023

Open Access
Cited by 26
Prognostic nomogram for bladder cancer with brain metastases: a National Cancer Database analysis.

J Transl Med, 2019

Open Access
Cited by 25
A comparative study of perioperative and survival outcomes of robot-assisted radical cystectomy in patients over 80 and under 80 years old.

World J Surg Oncol, 2021

Open Access
Cited by 24
Clinical validity of non-contrast-enhanced VI-RADS: prospective study using 3-T MRI with high-gradient magnetic field.

Eur Radiol, 2022

Open Access
Cited by 23
A radiomics-based interpretable machine learning model to predict the HER2 status in bladder cancer: a multicenter study.

Insights Imaging, 2024

Open Access
Cited by 22
Machine learning-based identification of tumor-infiltrating immune cell-associated model with appealing implications in improving prognosis and immunotherapy response in bladder cancer patients.

Front Immunol, 2023

Open Access
Cited by 22
Robot-assisted radical cystectomy and ileal conduit with Hugo RAS system: feasibility, setting and perioperative outcomes.

Int Braz J Urol, 2023

Open Access
Cited by 21
Differentiation of urothelial carcinoma in histopathology images using deep learning and visualization

J Pathol Inform, 2023

Open Access
Cited by 18
A Deep Learning System to Predict the Histopathological Results From Urine Cytopathological Images

Front Oncol, 2022

Open Access
Cited by 18
Deep Learning-Based Screening of Urothelial Carcinoma in Whole Slide Images of Liquid-Based Cytology Urine Specimens

Cancers (Basel), 2022

Open Access
Cited by 18
Semantic Segmentation of Urinary Bladder Cancer Masses from CT Images: A Transfer Learning Approach

Biology (Basel), 2021

Open Access
Cited by 17
Prediction of HER2 Status Based on Deep Learning in H&E-Stained Histopathology Images of Bladder Cancer

Biomedicines, 2024

Open Access
Cited by 16
Artificial Intelligence-Based Classification and Segmentation of Bladder Cancer in Cystoscope Images

Cancers (Basel), 2024

Open Access
Cited by 14
Leveraging Deep Learning in Real-Time Intelligent Bladder Tumor Detection During Cystoscopy: A Diagnostic Study

Ann Surg Oncol, 2025

Open Access
Cited by 12
Which data subset should be augmented for deep learning? a simulation study using urothelial cell carcinoma histopathology images

BMC Bioinformatics, 2023

Open Access
Cited by 9
Artificial Intelligence Reveals Distinct Prognostic Subgroups of Muscle-Invasive Bladder Cancer on Histology Images

Cancers (Basel), 2023

Open Access
Cited by 7
Artificial Intelligence as a Tool in the Diagnosis of Bladder Cancer: A Narrative Review

Cureus, 2025

Open Access
Cited by 5
A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides

J Pathol Clin Res, 2024

Open Access
Cited by 0
Innovative AI Model for Bladder Cancer Diagnosis

Discov Oncol, 2025

Open Access