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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Cancer
Last data update: Mar 28, 2024
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Records 1 - 26 (of 26 Records)
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Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center study.
Rui Sun et al. Insights Imaging 2024 15(1) 21
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Evaluation of a Natural Language Processing Model to Identify and Characterize Patients in the United States With High-Risk Non-Muscle-Invasive Bladder Cancer.
Vikram M Narayan et al. JCO Clin Cancer Inform 2023 7e2300096
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CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study.
Hongzheng Song et al. Cancer Imaging 2023 23(1) 89
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Real-time Detection of Bladder Cancer Using Augmented Cystoscopy with Deep Learning: a Pilot Study.
Timothy Chan Chang et al. J Endourol 2023
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Value of the application of computed tomography-based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer.
Situ Xiong et al. Cancer Med 2023
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Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.
Shaoxu Wu et al. The Lancet. Oncology 2023
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Bladder Cancer Radiation Oncology of the Future: Prognostic Modelling, Radiomics, and Treatment Planning With Artificial Intelligence.
Moore Nicholas S et al. Seminars in radiation oncology 2022 33(1) 70-75
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Radiomics Signature Using Manual Versus Automated Segmentation for Lymph Node Staging of Bladder Cancer.
Gresser Eva et al. European urology focus 2022
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Competitive Risk Model for Specific Mortality Prediction in Patients with Bladder Cancer: A Population-Based Cohort Study with Machine Learning.
Su Hao et al. Journal of oncology 2022 20229577904
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Uncovering additional predictors of urothelial carcinoma from voided urothelial cell clusters through a deep learning-based image preprocessing technique.
Levy Joshua J et al. Cancer cytopathology 2022
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Three-Dimensional Ultrasound Images in the Assessment of Bladder Tumor Health Monitoring under Deep Learning Algorithms.
Shao Changhua et al. Computational and mathematical methods in medicine 2022 20229170274
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Explainable artificial intelligence (XAI): closing the gap between image analysis and navigation in complex invasive diagnostic procedures.
O'Sullivan S et al. World journal of urology 2022
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A Fact-Finding Procedure Integrating Machine Learning and AHP Technique to Predict Delayed Diagnosis of Bladder Patients with Hematuria.
Lo Chia-Lun et al. Journal of healthcare engineering 2021 20213831453
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Usefulness of texture features of apparent diffusion coefficient maps in predicting chemoradiotherapy response in muscle-invasive bladder cancer.
Kimura Koichiro et al. European radiology 2021
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Role of Radiomics in the Prediction of Muscle-invasive Bladder Cancer: A Systematic Review and Meta-analysis.
Kozikowski Mieszko et al. European urology focus 2021
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The use of artificial intelligence for the diagnosis of bladder cancer: a review and perspectives.
Chan Erica On-Ting et al. Current opinion in urology 2021
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Clinical use of machine learning-based patho-mics signature for diagnosis and survival prediction of bladder cancer.
Chen Siteng et al. Cancer science 2021
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Bladder cancer in the time of machine learning: Intelligent tools for diagnosis and management.
Gandi Carlo et al. Urologia 2021 Jan 391560320987169
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Automatic recognition of bladder tumors using deep learning technology and its clinical application.
Yang Rui et al. The international journal of medical robotics + computer assisted surgery : MRCAS 2020 Oct e2194
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A deep learning network-assisted Bladder Tumor Recognition under Cystoscopy Based on Caffe Deep Learning Framework and EasyDL Platform.
Du Yang et al. The international journal of medical robotics + computer assisted surgery : MRCAS 2020 Sep
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Development of robust artificial neural networks for prediction of 5-year survival in bladder cancer.
Bhambhvani Hriday P et al. Urologic oncology 2020 Jun
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Multiresolution Application of Artificial Intelligence in Digital Pathology for Prediction of Positive Lymph Nodes From Primary Tumors in Bladder Cancer.
Harmon Stephanie A et al. JCO clinical cancer informatics 2020 Apr 4367-382
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Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects.
Negassi Misgana et al. World journal of urology 2020 Jan
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Study Progress of Radiomics With Machine Learning for Precision Medicine in Bladder Cancer Management.
Ge Lingling et al. Frontiers in oncology 2019 91296
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Artificial intelligence and neural networks in urology: current clinical applications.
Checcucci Enrico et al. Minerva urologica e nefrologica = The Italian journal of urology and nephrology 2019 Dec
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Support system of cystoscopic diagnosis for bladder cancer based on artificial intelligence.
Ikeda Atsushi et al. Journal of endourology 2019 Dec
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Page last reviewed:
Feb 1, 2024
Page last updated:
Mar 28, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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