Machine Learning Models as an Accurate Predictor of Survival in Pediatric Heart Transplant

被引：0
|
作者：
Brennan, Z. [1 ]
Sharaf, O. [2 ]
Emerson, D. [1 ]
Chikwe, J. [1 ]
Kim, R. [1 ]
Peek, G. [3 ]
Bleiweis, M. [3 ]
Jacobs, J. [3 ]
机构：
[1] Cedars Sinai Med Ctr, Los Angeles, CA USA
[2] Univ Florida, Coll Med, Gainesville, FL USA
[3] Univ Florida, Gainesville, FL USA
来源：
JOURNAL OF HEART AND LUNG TRANSPLANTATION | 2024年 / 43卷 / 04期
关键词：
D O I：
暂无
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
296
引用
收藏
页码：S154 / S154
页数：1
相关论文
共 50 条
  • [41] Machine learning models in breast cancer survival prediction
    Montazeri, Mitra
    Montazeri, Mohadeseh
    Montazeri, Mahdieh
    Beigzadeh, Amin
    TECHNOLOGY AND HEALTH CARE, 2016, 24 (01) : 31 - 42
  • [42] ACCURATE PREDICTION OF SURVIVAL IN GLIOBLASTOMA MULTIFORME. A MACHINE LEARNING TOOL
    Ruiz-Patino, A.
    NEURO-ONCOLOGY, 2017, 19 : 80 - 80
  • [43] The pediatric end-stage liver disease (PELD) model as a predictor of survival benefit and posttransplant survival in pediatric liver transplant recipients
    Barshes, NR
    Lee, TC
    Udell, IW
    O'Mahoney, CA
    Karpen, SJ
    Carter, BA
    Goss, JA
    LIVER TRANSPLANTATION, 2006, 12 (03) : 475 - 480
  • [44] Morbidity in Pediatric Heart Transplant Recipients: A Pediatric Heart Transplant Society Study
    Brosbe, Micah S.
    Wright, Lydia
    Pruitt, Elizabeth
    Dreyer, William J.
    Kirmani, Sonya
    Knight, Margaret
    Nakano, Stephanie
    Kindel, Steven J.
    Ryan, Thomas D.
    Kirklin, James K.
    Deshpande, Shriprasad R.
    CIRCULATION, 2018, 138
  • [45] EFFECTS OF POST TRANSPLANT FOLLOW UP FACILITY TYPE ON SURVIVAL IN PEDIATRIC HEART TRANSPLANT PATIENTS
    Chinnock, Richard
    Hess, Sarah
    PEDIATRIC TRANSPLANTATION, 2011, 15 : 76 - 77
  • [46] Machine Learning Models Show That Global Longitudinal Strain is a Strong Predictor of Survival After Echocardiography That is Superior to Ejection Fraction
    Agasthya, Greeshma
    Jing Linyuan
    Ulloa Cerna, Alvaro E.
    Samad, Manar D.
    Good, Christopher W.
    Bauch, Terry D.
    Haggerty, Christopher M.
    Fornwalt, Brandon K.
    CIRCULATION, 2018, 138
  • [47] Machine Learning vs. survival analysis models: a study on right censored heart failure data
    Srujana, B.
    Verma, Dhananjay
    Naqvi, Sameen
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2024, 53 (04) : 1899 - 1916
  • [48] Heart Disease Classification Using Machine Learning Models
    Folorunso, Sakinat Oluwabukonla
    Awotunde, Joseph Bamidele
    Adeniyi, Emmanuel Abidemi
    Abiodun, Kazeem Moses
    Ayo, Femi Emmanuel
    INFORMATICS AND INTELLIGENT APPLICATIONS, 2022, 1547 : 35 - 49
  • [49] Machine Learning Based Predictive Models Are More Accurate Than TNM Staging in Predicting Survival in Patients With Pancreatic Cancer
    Das, Amit
    Ngamruengphong, Saowanee
    AMERICAN JOURNAL OF GASTROENTEROLOGY, 2019, 114 : S48 - S48
  • [50] Ensemble of machine learning techniques to predict survival in kidney transplant recipients
    Díez-Sanmartín, Covadonga
    Sarasa Cabezuelo, Antonio
    Andrés Belmonte, Amado
    Computers in Biology and Medicine, 2024, 180
12345