MACHINE LEARNING BETTER PREDICTS RISK AFTER ACUTE CORONARY SYNDROMES, IDENTIFIES HIGH-COST INDIVIDUALS AND THOSE WITH ELEVATED BURDEN OF UNCONTROLLED RISK FACTORS

被引：0
|
作者：
de Carvalho, L. S. [1 ]
Miranda, R. G. S. [2 ]
Gioppato, S. [3 ]
Fernandez, M. [4 ]
Trindade, B. C. [5 ]
Quinaglia e Silva, J. C. [6 ]
Avila, S. [3 ]
Sposito, A. [3 ]
机构：
[1] Univ Estadual Campinas, Brasilia, DF, Brazil
[2] Brazilian Minist Econ, Brasilia, DF, Brazil
[3] Univ Estadual Campinas, Campinas, SP, Brazil
[4] Clar Healthcare Intelligence, Campinas, SP, Brazil
[5] Cornell Univ, Ithaca, NY USA
[6] Escola Super Ciencias Saude, Brasilia, DF, Brazil
来源：
VALUE IN HEALTH | 2019年 / 22卷
关键词：
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
PCV20
引用
收藏
页码：S545 / S545
页数：1
相关论文
共 7 条
  • [1] Machine Learning Predicts Cardiovascular Risk and Cost Burden After Acute Coronary Syndromes
    Carvalho, Luiz Sergio F.
    Gioppato, Silvio
    Fernandez, Marta D.
    Trindade, Bernardo C.
    Quinaglia e Silva, Jose Carlos
    Miranda, Rebeca G.
    Avila, Sandra
    Sposito, Andrei
    CIRCULATION, 2019, 140
  • [2] The framing of time-dependent machine learning models improves risk estimation among young individuals with acute coronary syndromes
    Luiz Sérgio Fernandes de Carvalho
    Gustavo Alexim
    Ana Claudia Cavalcante Nogueira
    Marta Duran Fernandez
    Tito Barbosa Rezende
    Sandra Avila
    Ricardo Torres Bispo Reis
    Alexandre Anderson Munhoz Soares
    Andrei Carvalho Sposito
    Scientific Reports, 13
  • [3] The framing of time-dependent machine learning models improves risk estimation among young individuals with acute coronary syndromes
    de Carvalho, Luiz Sergio Fernandes
    Alexim, Gustavo
    Nogueira, Ana Claudia Cavalcante
    Fernandez, Marta Duran
    Rezende, Tito Barbosa
    Avila, Sandra
    Reis, Ricardo Torres Bispo
    Soares, Alexandre Anderson Munhoz
    Sposito, Andrei Carvalho
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [4] The framing of time-dependent machine learning models improves risk estimation among young individuals with acute coronary syndromes
    Carvalho, L. S. F.
    Nogueira, A. C. C.
    Fernandez, M. D.
    Soares, A. A. M.
    Rezende, T. B.
    Avila, S. E. F.
    Alexim, G.
    Sposito, A. C.
    EUROPEAN HEART JOURNAL, 2023, 44
  • [5] THE FRAMING OF TIME-DEPENDENT MACHINE LEARNING MODELS IMPROVES RISK ESTIMATION AMONG YOUNG INDIVIDUALS WITH ACUTE CORONARY SYNDROMES
    de Carvalho, L. S.
    Nogueira, A. C. C.
    Fernandez, M.
    Sposito, A.
    VALUE IN HEALTH, 2023, 26 (06) : S50 - S50
  • [6] Heart-type fatty acid-binding protein predicts long-term mortality after acute coronary syndrome and identifies high-risk patients across the range of troponin values
    Kilcullen, Niamh
    Viswanathan, Karthik
    Das, Rajiv
    Morrell, Christine
    Farrin, Amanda
    Barth, Julian H.
    Hall, Alistair S.
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2007, 50 (21) : 2061 - 2067
  • [7] A NOVEL ENSEMBLE MACHINE LEARNING-BASED METHOD VERSUS CLINICAL RISK SCORING FOR DISCRIMINATION OF INDIVIDUALS WHO WILL VERSUS WILL NOT EXPERIENCE ACUTE CORONARY SYNDROME AFTER CORONARY COMPUTED TOMOGRAPHIC ANGIOGRAPHY: RESULTS FROM THE ICONIC STUDY
    Al'Aref, Subhi
    Maliakal, Gabriel
    Cheng, Michael
    Kolli, Kranthi
    Singh, Gurpreet
    Pandey, Mohit
    Kumar, Amit
    Dwivedi, Aeshita
    Andreini, Daniele
    Cademartiri, Filippo
    Chinnaiyan, Kavitha
    Chow, Benjamin
    Cury, Ricardo
    Feuchtner, Gudrun
    Hadamitzky, Martin
    Kim, Yong-Jin
    Leipsic, Jonathon
    Marques, Hugo
    Pontone, Gianluca
    Villines, Todd
    Berman, Daniel
    Budoff, Matthew
    Bax, Jeroen J.
    Chang, Hyuk-Jae
    Min, James K.
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2018, 71 (11) : 1628 - 1628
1