Improving risk stratification of recurrent myocardial infarction in a large real-world dataset using machine learning

被引:0
|
作者
Chodick, G. [1 ]
Vered, Z. [2 ]
Elgui, K. [3 ]
Mathieu, T. [3 ]
Trichelair, P. [3 ]
Zachlederova, M. [4 ]
Rousset, A. [5 ]
机构
[1] Maccabi Hlth Serv, Tel Aviv, Israel
[2] Tel Aviv Univ, Res Inst, Sackler Sch Med, Maccabi Hlth Serv, Tel Aviv, Israel
[3] Owkin Inc, New York, NY USA
[4] Amgen Sro, Prague, Czech Republic
[5] Amgen Inc, Thousand Oaks, CA USA
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
引用
收藏
页数:3
相关论文
共 50 条
  • [41] Predicting real-world response to mepolizumab in severe asthma using machine learning
    Usuba, Koyo
    Zhang, Lingjiao
    Liu, Xinyang
    Han, Tim
    Nightingale, Natalie
    Tehrani, Ali
    Zhang, Shiyuan
    Howarth, Peter
    Alfonso-Cristancho, Rafael
    EUROPEAN RESPIRATORY JOURNAL, 2024, 64
  • [42] Polygenic Risk Score and Statin Relative Risk Reduction for Primary Prevention of Myocardial Infarction in a Real-World Population
    Oni-Orisan, Akinyemi
    Haldar, Tanushree
    Cayabyab, Mari A. S.
    Ranatunga, Dilrini K.
    Hoffmann, Thomas J.
    Iribarren, Carlos
    Krauss, Ronald M.
    Risch, Neil
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2022, 112 (05) : 1070 - 1078
  • [43] A Review of Machine Learning Classification Using Quantum Annealing for Real-World Applications
    Nath R.K.
    Thapliyal H.
    Humble T.S.
    SN Computer Science, 2021, 2 (5)
  • [44] Using machine learning on real-world data to predict metastatic status.
    Green, Foad H.
    Huang, Hu T.
    Lerman, Michelle
    Tran, Mary
    Subramanian, Vinod
    Loving, Joshua
    Rioth, Matthew J.
    JOURNAL OF CLINICAL ONCOLOGY, 2022, 40 (16)
  • [45] Association Between Myopia and Pupil Diameter in Preschoolers: Evidence from a Machine Learning Approach Based on a Real-World Large-Scale Dataset
    Xu, Shengsong
    Li, Linling
    Han, Wenjing
    Zhu, Yingting
    Hu, Yin
    Li, Zhidong
    Ruan, Zhenbang
    Zhou, Zhuandi
    Zhuo, Yehong
    Fu, Min
    Yang, Xiao
    OPHTHALMOLOGY AND THERAPY, 2024, 13 (07) : 2009 - 2022
  • [46] Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care
    Chandran, Urmila
    Reps, Jenna
    Yang, Robert
    Vachani, Anil
    Maldonado, Fabien
    Kalsekar, Iftekhar
    CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2023, 32 (03) : 337 - 343
  • [47] Improving accuracy and efficiency in plant detection on a novel, benchmarking real-world dataset
    Ohnemuller, Laurenz
    Briassouli, Alexia
    2021 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY (IEEE METROAGRIFOR 2021), 2021, : 172 - 176
  • [48] Underwater Image Restoration via Contrastive Learning and a Real-World Dataset
    Han, Junlin
    Shoeiby, Mehrdad
    Malthus, Tim
    Botha, Elizabeth
    Anstee, Janet
    Anwar, Saeed
    Wei, Ran
    Armin, Mohammad Ali
    Li, Hongdong
    Petersson, Lars
    REMOTE SENSING, 2022, 14 (17)
  • [49] Using machine learning to identify risk factors for pancreatic cancer: a retrospective cohort study of real-world data
    Su, Na
    Tang, Rui
    Zhang, Yice
    Ni, Jiaqi
    Huang, Yimei
    Liu, Chunqi
    Xiao, Yuzhou
    Zhu, Baoting
    Zhao, Yinglan
    FRONTIERS IN PHARMACOLOGY, 2024, 15
  • [50] Evaluation of a Deep Learning Model on a Real-World Clinical Glaucoma Dataset
    Thakoor, Kaveri
    Leshno, Ari
    La Bruna, Sol
    Tsamis, Emmanouil
    De Moraes, Gustavo
    Sajda, Paul
    Harizman, Noga
    Liebmann, Jeffrey M.
    Cioffi, George A.
    Hood, Donald C.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2022, 63 (07)