USING ARTIFICIAL INTELLIGENCE AND MACHINE-LEARNING ALGORITHMS WITH GENE EXPRESSION PROFILING TO PREDICT SUPERFICIAL BLADDER CANCER RECURRENCE AT INITIAL PRESENTATION

被引：0
|
作者：
Mitra, Anirban P.
Bartsch, Georg, Jr.
Mitra, Sheetal A.
Almal, Arpit A.
Steven, Kenneth E.
Fry, David W.
Lenehan, Peter F.
Cote, Richard J.
Worzel, William P.
机构：
来源：
JOURNAL OF UROLOGY | 2012年 / 187卷 / 04期
关键词：
D O I：
10.1016/j.juro.2012.02.982
中图分类号：
R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];
学科分类号：
1002 ; 100201 ;
摘要：
887
引用
收藏
页码：E361 / E361
页数：1
相关论文
共 50 条
  • [41] Erratum to: Gene expression profiling to predict the risk of locoregional recurrence in breast cancer: a pooled analysis
    C. A. Drukker
    S. G. Elias
    M. V. Nijenhuis
    J. Wesseling
    H. Bartelink
    P. Elkhuizen
    B. Fowble
    P. W. Whitworth
    R. R. Patel
    F. A. de Snoo
    L. J. van’t Veer
    P. D. Beitsch
    E. J. Th. Rutgers
    Breast Cancer Research and Treatment, 2015, 149 : 567 - 567
  • [42] Improving gene array analysis: The application of artificial intelligence identifies novel biomarkers of superficial bladder cancer progression
    Catto, J.
    Abbod, M.
    Linkens, D.
    Wild, P.
    Herr, A.
    Wissman, C. S.
    Pilarsky, C.
    Hartmann, A.
    Hamdy, F.
    EUROPEAN UROLOGY SUPPLEMENTS, 2007, 6 (02) : 118 - 118
  • [43] The Use of Gene Expression Profiling to Predict Molecular Subtypes of Breast Cancer by a New Machine Learning Algorithm: Random Forest
    Fararjeh, Abdul-Fattah
    Al-khlifeh, Enas
    Aloliqi, Abdulaziz A.
    Tarawneh, Ahmad S.
    Hassanat, Ahmad B.
    CURRENT BIOINFORMATICS, 2024,
  • [44] A Robust Procedure for Machine Learning Algorithms Using Gene Expression Data
    Auwul, Md Rabiul
    Zhang, Chongqi
    Shahjaman, Md
    BIOINTERFACE RESEARCH IN APPLIED CHEMISTRY, 2022, 12 (02): : 2422 - 2439
  • [45] Reply to "Harnessing machine learning to predict colorectal cancer metastasis: A promising artificial intelligence frontier"
    Guo, Zhentian
    Zhang, Zongming
    EJSO, 2024, 50 (11):
  • [46] Machine learning and explainable artificial intelligence to predict pathologic stage in men with localized prostate cancer
    Semwal, Hemal
    Ladbury, Colton
    Sabbagh, Ali
    Mohamad, Osama
    Tilki, Derya
    Amini, Arya
    Wong, Jeffrey
    Li, Yun Rose
    Glaser, Scott
    Yuh, Bertram
    Dandapani, Savita
    PROSTATE, 2024,
  • [47] Machine Learning and Explainable Artificial Intelligence to Predict Occult Pelvic Nodal Metastases in Prostate Cancer
    Semwal, H.
    Ladbury, C. J.
    Hao, C.
    Amini, A.
    Wong, J. Y. C.
    Li, R.
    Glaser, S. M.
    Dandapani, S. V.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2023, 117 (02): : E435 - E435
  • [48] An artificial intelligence system using machine-learning for automatic detection and classification of dental restorations in panoramic radiography
    Abdalla-Aslan, Ragda
    Yeshua, Talia
    Kabla, Daniel
    Leichter, Isaac
    Nadler, Chen
    ORAL SURGERY ORAL MEDICINE ORAL PATHOLOGY ORAL RADIOLOGY, 2020, 130 (05): : 593 - 602
  • [49] Comparative Analysis to Predict Breast Cancer using Machine Learning Algorithms: A Survey
    Thomas, Tanishk
    Pradhan, Nitesh
    Dhaka, Vijaypal Singh
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT-2020), 2020, : 192 - 196
  • [50] Predicting risk of breast cancer recurrence using gene-expression profiling
    Ignatiadis, Michail
    Desmedt, Cbristine
    PHARMACOGENOMICS, 2007, 8 (01) : 101 - 111
12345