Improving Mortality Predictions for Patients With Mechanical Circulatory Support Using Follow-Up Data and Machine Learning

被引：4
|
作者：
Jaeger, Byron C. [1 ]
Cantor, Ryan S. [1 ]
Sthanam, Venkata [1 ]
Rudraraju, Ramaraju [1 ]
机构：
[1] Univ Alabama Birmingham, Kirklin Inst Res Surg Outcomes, 703 19th St S, Birmingham, AL 35233 USA
来源：
CIRCULATION-GENOMIC AND PRECISION MEDICINE | 2020年 / 13卷 / 02期
关键词：
health care; heart-assist devices; humans; machine learning; outcome assessment;
D O I：
10.1161/CIRCGEN.119.002877
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
[No abstract available]
引用
收藏
页数：2
相关论文
共 50 条
  • [21] Machine Learning Outperforms Existing Methods to Predict Post-Operative Mortality in Patients Bridged to Heart Transplantation with Temporary Mechanical Circulatory Support
    Shou, B. L.
    Russel, J. W.
    Ong, C.
    Lewis, T.
    Zhou, A. L.
    Verma, A.
    Benharash, P.
    Choi., C.
    JOURNAL OF HEART AND LUNG TRANSPLANTATION, 2022, 41 (04): : S28 - S29
  • [22] Pre-operative Machine Learning for Heart Transplant Patients Bridged with Temporary Mechanical Circulatory Support
    Shou, Benjamin L.
    Chatterjee, Devina
    Russel, Joseph W.
    Zhou, Alice L.
    Florissi, Isabella S.
    Lewis, Tabatha
    Verma, Arjun
    Benharash, Peyman
    Choi, Chun Woo
    JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE, 2022, 9 (09)
  • [23] Follow-up study on mortality in Korean stroke patients
    Im, Jee Hye
    Lee, Kun Sei
    Kim, Keon Yeop
    Hong, Nam Soo
    Lee, Sang Won
    Bae, Hee Joon
    JOURNAL OF THE KOREAN MEDICAL ASSOCIATION, 2011, 54 (11): : 1199 - 1208
  • [24] Supervised Machine Learning to Predict Follow-Up Among Adjuvant Endocrine Therapy Patients
    Harrell, Morgan
    Levy, Mia
    Fabbri, Daniel
    2017 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI), 2017, : 490 - 495
  • [25] Improving Electron Density Predictions in the Topside of the Ionosphere Using Machine Learning on In Situ Satellite Data
    Dutta, S.
    Cohen, M. B.
    SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS, 2022, 20 (09):
  • [26] Improving machine learning predictions to estimate fishing effort using vessel's tracking data
    Samarao, J.
    Moreno, A.
    Gaspar, M. B.
    Rufino, M. M.
    ECOLOGICAL INFORMATICS, 2025, 85
  • [27] Machine learning-assisted prediction of trabeculectomy outcomes among patients of juvenile glaucoma by using 5-year follow-up data
    Birla, Shweta
    Varshney, Toshit
    Singh, Abhishek
    Sharma, Arun
    Panigrahi, Arnav
    Gupta, Shikha
    Gupta, Dinesh
    Gupta, Viney
    INDIAN JOURNAL OF OPHTHALMOLOGY, 2024, 72 (07) : 987 - 993
  • [28] Clinical follow-up of patients with transient circulatory support with a percutaneous left ventricular assist device (TANDEMTM heart)
    Hullin, R.
    Schmid, M.
    Jakob, S.
    Rothen, H. U.
    Takala, J.
    Carrel, T.
    Meier, B.
    Windecker, S.
    EUROPEAN HEART JOURNAL, 2005, 26 : 514 - 514
  • [29] Macroeconomic Predictions Using Payments Data and Machine Learning
    Chapman, James T. E.
    Desai, Ajit
    FORECASTING, 2023, 5 (04): : 652 - 683
  • [30] Machine Learning to Optimize the Echocardiographic Follow-Up of Aortic Stenosis
    Sanchez-Puente, Antonio
    Dorado-Diaz, Ignacio
    Sampedro-Gomez, Jesus
    Bermejo, Javier
    Martinez-Legazpi, Pablo
    Fernandez-Aviles, Francisco
    Sanchez-Gonzalez, Javier
    del Villar, Candelas Perez
    Vicente-Palacios, Victor
    Sanchez, Pedro L.
    JACC-CARDIOVASCULAR IMAGING, 2022, 16 (06) : 733 - 744
12345