These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

747 related articles for article (PubMed ID: 37001474)

  • 1. Machine learning prediction models and nomogram to predict the risk of in-hospital death for severe DKA: A clinical study based on MIMIC-IV, eICU databases, and a college hospital ICU.
    Xie W; Li Y; Meng X; Zhao M
    Int J Med Inform; 2023 Jun; 174():105049. PubMed ID: 37001474
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Nomogram to predict the risk of acute kidney injury in patients with diabetic ketoacidosis: an analysis of the MIMIC-III database.
    Fan T; Wang H; Wang J; Wang W; Guan H; Zhang C
    BMC Endocr Disord; 2021 Mar; 21(1):37. PubMed ID: 33663489
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Clinical nomogram prediction model to assess the risk of prolonged ICU length of stay in patients with diabetic ketoacidosis: a retrospective analysis based on the MIMIC-IV database.
    Shi J; Chen F; Zheng K; Su T; Wang X; Wu J; Ni B; Pan Y
    BMC Anesthesiol; 2024 Feb; 24(1):86. PubMed ID: 38424557
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.
    Wang Y; Sun X; Lu J; Zhong L; Yang Z
    Ann Med; 2024 Dec; 56(1):2388709. PubMed ID: 39155811
    [TBL] [Abstract][Full Text] [Related]  

  • 5. [Constructing a predictive model for the death risk of patients with septic shock based on supervised machine learning algorithms].
    Xie Z; Jin J; Liu D; Lu S; Yu H; Han D; Sun W; Huang M
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2024 Apr; 36(4):345-352. PubMed ID: 38813626
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Development and validation of a nomogram for predicting in-hospital mortality of patients with cervical spine fractures without spinal cord injury.
    Xing Z; Cai L; Wu Y; Shen P; Fu X; Xu Y; Wang J
    Eur J Med Res; 2024 Jan; 29(1):80. PubMed ID: 38287435
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction model of in-hospital mortality in intensive care unit patients with cardiac arrest: a retrospective analysis of MIMIC -IV database based on machine learning.
    Sun Y; He Z; Ren J; Wu Y
    BMC Anesthesiol; 2023 May; 23(1):178. PubMed ID: 37231340
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development and Internal Validation of a Nomogram to Predict Mortality During the ICU Stay of Thoracic Fracture Patients Without Neurological Compromise: An Analysis of the MIMIC-III Clinical Database.
    Wang H; Ou Y; Fan T; Zhao J; Kang M; Dong R; Qu Y
    Front Public Health; 2021; 9():818439. PubMed ID: 35004604
    [No Abstract]   [Full Text] [Related]  

  • 9. Development and validation of a nomogram for predicting in-hospital mortality in patients with nonhip femoral fractures.
    Xing Z; Xu Y; Wu Y; Fu X; Shen P; Che W; Wang J
    Eur J Med Res; 2023 Nov; 28(1):539. PubMed ID: 38001553
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A simple APACHE IV risk dynamic nomogram that incorporates early admitted lactate for the initial assessment of 28-day mortality in critically ill patients with acute myocardial infarction.
    Song J; Yu T; Yan Q; Wu L; Li S; Wang L
    BMC Cardiovasc Disord; 2022 Nov; 22(1):502. PubMed ID: 36434509
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Nomogram predictive model for in-hospital mortality risk in elderly ICU patients with urosepsis.
    Wei J; Liang R; Liu S; Dong W; Gao J; Hua T; Xiao W; Li H; Zhu H; Hu J; Cao S; Liu Y; Lyu J; Yang M
    BMC Infect Dis; 2024 Apr; 24(1):442. PubMed ID: 38671376
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Development of a novel tool: a nomogram for predicting in-hospital mortality of patients in intensive care unit after percutaneous coronary intervention.
    Yuan M; Ren BC; Wang Y; Ren F; Gao D
    BMC Anesthesiol; 2023 Jan; 23(1):5. PubMed ID: 36609220
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting the risk factors of diabetic ketoacidosis-associated acute kidney injury: A machine learning approach using XGBoost.
    Fan T; Wang J; Li L; Kang J; Wang W; Zhang C
    Front Public Health; 2023; 11():1087297. PubMed ID: 37089510
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prediction model of in-hospital mortality in intensive care unit patients with heart failure: machine learning-based, retrospective analysis of the MIMIC-III database.
    Li F; Xin H; Zhang J; Fu M; Zhou J; Lian Z
    BMJ Open; 2021 Jul; 11(7):e044779. PubMed ID: 34301649
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development and validation a nomogram prediction model for early diagnosis of bloodstream infections in the intensive care unit.
    Qi Z; Dong L; Lin J; Duan M
    Front Cell Infect Microbiol; 2024; 14():1348896. PubMed ID: 38500500
    [TBL] [Abstract][Full Text] [Related]  

  • 16. [Establishment and evaluation of early in-hospital death prediction model for patients with acute pancreatitis in intensive care unit].
    Yu L; Zhou X; Li Y; Liu M
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Aug; 35(8):865-869. PubMed ID: 37593868
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Interpretable machine learning model for early prediction of 28-day mortality in ICU patients with sepsis-induced coagulopathy: development and validation.
    Zhou S; Lu Z; Liu Y; Wang M; Zhou W; Cui X; Zhang J; Xiao W; Hua T; Zhu H; Yang M
    Eur J Med Res; 2024 Jan; 29(1):14. PubMed ID: 38172962
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine learning-based in-hospital mortality risk prediction tool for intensive care unit patients with heart failure.
    Chen Z; Li T; Guo S; Zeng D; Wang K
    Front Cardiovasc Med; 2023; 10():1119699. PubMed ID: 37077747
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predictive nomogram for 28-day mortality risk in mitral valve disorder patients in the intensive care unit: A comprehensive assessment from the MIMIC-III database.
    Qiu Y; Li M; Song X; Li Z; Ma A; Meng Z; Li Y; Tan M
    Int J Cardiol; 2024 Jul; 407():132105. PubMed ID: 38677334
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine learning for prediction of in-hospital mortality in lung cancer patients admitted to intensive care unit.
    Huang T; Le D; Yuan L; Xu S; Peng X
    PLoS One; 2023; 18(1):e0280606. PubMed ID: 36701342
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 38.