Survival prediction models: an introduction to discrete-time modeling

被引：0
|
作者：
Krithika Suresh
Cameron Severn
Debashis Ghosh
机构：
[1] Colorado School of Public Health,Department of Biostatistics and Informatics
[2] University of Colorado Anschutz Medical Campus,Child Health Biostatistics Core Department of Pediatrics, Section of Endocrinology, School of Medicine
来源：
BMC Medical Research Methodology | / 22卷
关键词：
Cox proportional hazards; Machine learning; Random survival forest; Time-to-event;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [41] Idle Time Window Prediction in Cellular Networks With Deep Spatiotemporal Modeling
    Fang, Luoyang
    Cheng, Xiang
    Wang, Haonan
    Yang, Liuqing
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2019, 37 (06) : 1441 - 1454
  • [42] Quantitative Analysis of Anesthesia Recovery Time by Machine Learning Prediction Models
    Yang, Shumin
    Li, Huaying
    Lin, Zhizhe
    Song, Youyi
    Lin, Cheng
    Zhou, Teng
    MATHEMATICS, 2022, 10 (15)
  • [43] Personalized prediction of survival rate with combination of penalized Cox models in patients with colorectal cancer
    Lee, Seon Hwa
    Cha, Jae Myung
    Shin, Seung Jun
    MEDICINE, 2024, 103 (24) : e38584
  • [44] A new algorithm for time series prediction using machine learning models
    Jahnavi, Yeturu
    Elango, Poongothai
    Raja, S. P.
    Parra Fuente, Javier
    Verdu, Elena
    EVOLUTIONARY INTELLIGENCE, 2023, 16 (05) : 1449 - 1460
  • [45] Comparing hundreds of machine learning and discrete choice models for travel demand modeling: An empirical benchmark
    Wang, Shenhao
    Mo, Baichuan
    Zheng, Yunhan
    Hess, Stephane
    Zhao, Jinhua
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2024, 190
  • [46] Modeling time-to-event (survival) data using classification tree analysis
    Linden, Ariel
    Yarnold, Paul R.
    JOURNAL OF EVALUATION IN CLINICAL PRACTICE, 2017, 23 (06) : 1299 - 1308
  • [47] SurvSHAP(t): Time-dependent explanations of machine learning survival models
    Krzyzinski, Mateusz
    Spytek, Mikolaj
    Baniecki, Hubert
    Biecek, Przemyslaw
    KNOWLEDGE-BASED SYSTEMS, 2023, 262
  • [48] Time-dependent interpretable survival prediction model for second primary NSCLC patients
    Luo, Qiong
    Zhang, Qianyuan
    Liu, Haiyu
    Chen, Xiangqi
    Yang, Sheng
    Xu, Qian
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2025, 195
  • [49] Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques
    Pate, Alexander
    Sperrin, Matthew
    Riley, Richard D.
    Sergeant, Jamie C.
    Van Staa, Tjeerd
    Peek, Niels
    Mamas, Mamas A.
    Lip, Gregory Y. H.
    O'Flaherty, Martin
    Buchan, Iain
    Martin, Glen P.
    STATISTICS IN MEDICINE, 2023, 42 (18) : 3184 - 3207
  • [50] A Comparison of GPU Execution Time Prediction using Machine Learning and Analytical Modeling
    Amaris, Marcos
    de Camargo, Raphael Y.
    Dyab, Mohamed
    Goldman, Alfredo
    Trystram, Denis
    15TH IEEE INTERNATIONAL SYMPOSIUM ON NETWORK COMPUTING AND APPLICATIONS (IEEE NCA 2016), 2016, : 326 - 333
12345