Using artificial intelligence to predict adverse outcomes in emergency department patients with hyperglycemic crises in real time

被引：0
作者：
Chin-Chuan Hsu
Yuan Kao
Chien-Chin Hsu
Chia-Jung Chen
Shu-Lien Hsu
Tzu-Lan Liu
Hung-Jung Lin
Jhi-Joung Wang
Chung-Feng Liu
Chien-Cheng Huang
机构：
[1] Chi Mei Medical Center,Department of Emergency Medicine
[2] College of Health Sciences,Graduate Institute of Medical Sciences
[3] Chang Jung Christian University, School of Medicine, College of Medicine
[4] National Sun Yat-sen university,Information Systems
[5] Chi Mei Medical Center,Department of Nursing
[6] Chi Mei Medical Center,Department of Emergency Medicine
[7] Taipei Medical University,Department of Anesthesiology
[8] Chi Mei Medical Center,Department of Anesthesiology
[9] National Defense Medical Center,Department of Medical Research
[10] Chi Mei Medical Center,Department of Emergency Medicine
[11] Kaohsiung Medical University,Department of Environmental and Occupational Health, College of Medicine
[12] National Cheng Kung University,undefined
来源：
BMC Endocrine Disorders | / 23卷
关键词：
Adverse outcome; Artificial intelligence; Emergency department; Hyperglycemic crises; Intensive care unit; Machine learning; Mortality; Multilayer perceptron; Sepsis;
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] Artificial Intelligence Algorithms and Natural Language Processing for the Recognition of Syncope Patients on Emergency Department Medical Records
    Dipaola, Franca
    Gatti, Mauro
    Pacetti, Veronica
    Bottaccioli, Anna Giulia
    Shiffer, Dana
    Minonzio, Maura
    Mene, Roberto
    Levra, Alessandro Giaj
    Solbiati, Monica
    Costantino, Giorgio
    Anastasio, Marco
    Sini, Elena
    Barbic, Franca
    Brunetta, Enrico
    Furlan, Raffaello
    JOURNAL OF CLINICAL MEDICINE, 2019, 8 (10)
  • [32] A study of "left against medical advice" emergency department patients: an optimized explainable artificial intelligence framework
    Ahmed, Abdulaziz
    Aram, Khalid Y.
    Tutun, Salih
    Delen, Dursun
    HEALTH CARE MANAGEMENT SCIENCE, 2024, 27 (04) : 485 - 502
  • [33] Trauma outcome predictor: An artificial intelligence interactive smartphone tool to predict outcomes in trauma patients
    Maurer, Lydia R.
    Bertsimas, Dimitris
    Bouardi, Hamza Tazi
    El Hechi, Majed
    El Moheb, Mohamad
    Giannoutsou, Katerina
    Zhuo, Daisy
    Dunn, Jack
    Velmahos, George C.
    Kaafarani, Haytham M. A.
    JOURNAL OF TRAUMA AND ACUTE CARE SURGERY, 2021, 91 (01) : 93 - 99
  • [34] Improvement of the Identification of Seniors at Risk scale for predicting adverse health outcomes of elderly patients in the emergency department
    Hsu, Chin-Wang
    Lee, Ching-Wei
    Hsu, Shih-Chang
    Huang, Wen-Cheng
    Hsu, Yuan-Pin
    Chi, Mei-Ju
    INTERNATIONAL EMERGENCY NURSING, 2023, 68
  • [35] A study of “left against medical advice” emergency department patients: an optimized explainable artificial intelligence frameworkA study of “left against medical advice” emergency department patients: an optimized explainable artificial intelligence frameworkA. Ahmed et al.
    Abdulaziz Ahmed
    Khalid Y. Aram
    Salih Tutun
    Dursun Delen
    Health Care Management Science, 2024, 27 (4) : 485 - 502
  • [36] Risk Factors for Adverse Outcomes in Adult and Pediatric Patients With Hyperglycemia Presenting to the Emergency Department: A Systematic Review
    Siddiqi, Lubna
    VanAarsen, Kristine
    Iansavichene, Alla
    Yan, Justin
    CANADIAN JOURNAL OF DIABETES, 2019, 43 (05) : 361 - +
  • [37] Initial outcomes using a novel bedwetting alarm (Gogoband®) that utilizes real time artificial intelligence to wake users prior to wetting
    Franco, Israel
    Coble, Jon
    JOURNAL OF PEDIATRIC UROLOGY, 2023, 19 (05) : 557.e1 - 557.e8
  • [38] Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms
    Bousson, Valerie
    Attane, Gregoire
    Benoist, Nicolas
    Perronne, Laetitia
    Diallo, Abdourahmane
    Hadid-Beurrier, Lama
    Martin, Emmanuel
    Hamzi, Lounis
    Duval, Arnaud Depil
    Revue, Eric
    Vicaut, Eric
    Salvat, Cecile
    ACADEMIC RADIOLOGY, 2023, 30 (10) : 2118 - 2139
  • [39] Real-life benefit of artificial intelligence-based fracture detection in a pediatric emergency department
    Ziegner, Maria
    Pape, Johanna
    Lacher, Martin
    Brandau, Annika
    Kelety, Tibor
    Mayer, Steffi
    Hirsch, Franz Wolfgang
    Rosolowski, Maciej
    Grafe, Daniel
    EUROPEAN RADIOLOGY, 2025,
  • [40] Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial
    Balmin, Joel
    Villani, Patrick
    Gay, Mathias
    Fabries, Stephane
    Havreng-Thery, Charlotte
    Malvoisin, Stephanie
    Denis, Fabrice
    Veyron, Jacques-Henri
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2022, 24 (09)
12345