Combining structured and unstructured data for predictive models: a deep learning approach

被引:0
|
作者
Dongdong Zhang
Changchang Yin
Jucheng Zeng
Xiaohui Yuan
Ping Zhang
机构
[1] The Ohio State University,Department of Biomedical Informatics
[2] Wuhan University of Technology,School of Computer Science and Technology
[3] The Ohio State University,Department of Computer Science and Engineering
来源
BMC Medical Informatics and Decision Making | / 20卷
关键词
Electronic health records; Deep learning; Data fusion; Time series forecasting;
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
  • [31] A Deep Learning Approach for Predictive Healthcare Process Monitoring
    Ramirez-Alcocer, Ulises Manuel
    Tello-Leal, Edgar
    Romero, Gerardo
    Macias-Hernandez, Barbara A.
    INFORMATION, 2023, 14 (09)
  • [32] Data Analysis for Predictive Maintenance Using Time Series and Deep Learning Models-A Case Study in a Pulp Paper Industry
    Mateus, Balduino
    Mendes, Mateus
    Farinha, Jose Torres
    Martins, Alexandre Batista
    Cardoso, Antonio Marques
    PROCEEDINGS OF INCOME-VI AND TEPEN 2021: PERFORMANCE ENGINEERING AND MAINTENANCE ENGINEERING, 2023, 117 : 11 - 25
  • [33] Detection of Data Matrix Encoded Landmarks in Unstructured Environments using Deep Learning
    Almeida, Tiago
    Santos, Vitor
    Lourenco, Bernardo
    Fonseca, Pedro
    2020 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2020), 2020, : 74 - 80
  • [34] Deep Learning Approach Combining GAN and BiGRU for Diabetes Prediction
    Fatima, Tehreem
    Yang, Wenbiao
    Xia, Kewen
    Zia, Syed Muhammad Khalid Bin
    2024 3RD INTERNATIONAL CONFERENCE ON ROBOTICS, ARTIFICIAL INTELLIGENCE AND INTELLIGENT CONTROL, RAIIC 2024, 2024, : 346 - 349
  • [35] Gradient-Boosted Based Structured and Unstructured Learning
    Gavito, Andrea Trevino
    Klabjan, Diego
    Utke, Jean
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2023, PT III, 2023, 14256 : 439 - 451
  • [36] A deep learning approach of financial distress recognition combining text
    Li, Jiawang
    Wang, Chongren
    ELECTRONIC RESEARCH ARCHIVE, 2023, 31 (08): : 4683 - 4707
  • [37] Evaluating the Rate of Penetration With Deep-Learning Predictive Models
    Lee, Cheolhwan
    Kim, Jongkook
    Kim, Namjoong
    Ki, Seil
    Seo, Jeonggyu
    Park, Changhyup
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2025, 2025 (01)
  • [38] Deep learning approach to creating bone models
    Krawczyk, Zuzanna
    Starzynski, Jacek
    PROCEEDINGS OF 2020 IEEE 21ST INTERNATIONAL CONFERENCE ON COMPUTATIONAL PROBLEMS OF ELECTRICAL ENGINEERING (CPEE), 2020,
  • [39] Learning deep autoregressive models for hierarchical data
    Andersson, Carl R.
    Wahlstrom, Niklas
    Schon, Thomas B.
    IFAC PAPERSONLINE, 2021, 54 (07): : 529 - 534
  • [40] A Proposed Approach for Object Detection and Recognition by Deep Learning Models Using Data Augmentation
    Abdulkareem, Ismael M.
    AL-Shammri, Faris K.
    Khalid, Noor Aldeen A.
    Omran, Natiq A.
    INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING, 2024, 20 (05) : 31 - 43