The 30-days hospital readmission risk in diabetic patients: predictive modeling with machine learning classifiers

被引:0
|
作者
Yujuan Shang
Kui Jiang
Lei Wang
Zheqing Zhang
Siwei Zhou
Yun Liu
Jiancheng Dong
Huiqun Wu
机构
[1] Medical School of Nantong University,Department of Medical Informatics
[2] Children’s Hospital of Fudan University,Department of Statistics and Data Management
[3] the First Affiliated Hospital,Department of Information
[4] Nanjing Medical University,Department of Medical Informatics, School of Biomedical Engineering and Informatics
[5] Nanjing Medical University,undefined
来源
BMC Medical Informatics and Decision Making | / 21卷
关键词
Prediction model; Readmission; Diabetes; Machine learning;
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
  • [41] Readmission within 30-days of open reduction and internal fixation for ankle fractures: NSQIP analysis of 29,905 patients
    Sharma, Aadi
    Wyatt, Phillip B.
    Reiter, Charles R.
    Anastasio, Albert
    Satalich, James
    O'Neill, Conor N.
    Patel, Tejas
    Hanselman, Andrew
    Adams, Samuel
    Liles, Jeffrey
    Schweitzer, Karl
    JOURNAL OF ORTHOPAEDIC SURGERY AND RESEARCH, 2024, 19 (01):
  • [42] Predictive risk modelling for early hospital readmission of patients with diabetes in India
    Duggal, Reena
    Shukla, Suren
    Chandra, Sarika
    Shukla, Balvinder
    Khatri, Sunil Kumar
    INTERNATIONAL JOURNAL OF DIABETES IN DEVELOPING COUNTRIES, 2016, 36 (04) : 519 - 528
  • [43] Validation of a Predictive Model to Identify Patients at High Risk for Hospital Readmission
    Spiva, LeeAnna
    Hand, Marti
    VanBrackle, Lewis
    McVay, Frank
    JOURNAL FOR HEALTHCARE QUALITY, 2016, 38 (01) : 34 - 41
  • [44] Predictive risk modelling for early hospital readmission of patients with diabetes in India
    Reena Duggal
    Suren Shukla
    Sarika Chandra
    Balvinder Shukla
    Sunil Kumar Khatri
    International Journal of Diabetes in Developing Countries, 2016, 36 : 519 - 528
  • [45] Predictive factors leading to readmission within 30 days in patients undergoing surgery for spinal metastases
    Kumar, Jay I.
    Yanamadala, Vijay
    Shankar, Ganesh
    Choi, Bryan
    Shin, John
    JOURNAL OF NEUROSURGERY, 2018, 128 (04) : 18 - 18
  • [46] Prediction of hospital readmission of multimorbid patients using machine learning models
    Le Lay, Jules
    Alfonso-Lizarazo, Edgar
    Augusto, Vincent
    Bongue, Bienvenu
    Masmoudi, Malek
    Xie, Xiaolan
    Gramont, Baptiste
    Celarier, Thomas
    PLOS ONE, 2022, 17 (12):
  • [47] Predictive Modeling of 30-day Readmission of Heart Failure Patients Using Admit Labs, Early Clinical Tests, and History and Physical Exam for In-Hospital Modification of Readmission Risk
    Horne, Benjamin D.
    Budge, Deborah
    Benuzillo, Jose C.
    Bradshaw, Alejandra
    Bair, Tami L.
    Roberts, Colleen A.
    Rasmusson, Kismet D.
    Nixon, Jen
    Alharethi, Rami
    Kfoury, Abdallah G.
    Lappe, Donald L.
    CIRCULATION, 2013, 128 (22)
  • [48] Machine Learning-based Risk of Hospital Readmissions: Predicting Acute Readmissions within 30 Days of Discharge
    Baig, Mirza Mansoor
    Hua, Ning
    Zhang, Edmond
    Robinson, Reece
    Armstrong, Delwyn
    Whittaker, Robyn
    Robinson, Tom
    Mirza, Farhaan
    Ullah, Ehsan
    2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2019, : 2178 - 2181
  • [49] Predicting the Risk of Unplanned Readmission at 30 Days After PCI: Development and Validation of a New Predictive Nomogram
    Xu, Wenjun
    Tu, Hui
    Xiong, Xiaoyun
    Peng, Ying
    Cheng, Ting
    CLINICAL INTERVENTIONS IN AGING, 2022, 17 : 1013 - 1023
  • [50] PREDICTIVE MODELING OF THE 30-DAY BEHAVIORAL HEALTH READMISSION RISK IN A MEDICAID POPULATION
    Tanwar, S.
    Cui, C.
    Stephey, C.
    VALUE IN HEALTH, 2022, 25 (07) : S525 - S525