120 related articles for article (PubMed ID: 37712768)
1. Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm.
Ren W; Zou K; Huang S; Xu H; Zhang W; Shi X; Shi L; Zhong X; Peng Y; Tang X; Lü M
J Clin Gastroenterol; 2024 Jul; 58(6):619-626. PubMed ID: 37712768
[TBL] [Abstract][Full Text] [Related]
2. Interpretable machine learning for 28-day all-cause in-hospital mortality prediction in critically ill patients with heart failure combined with hypertension: A retrospective cohort study based on medical information mart for intensive care database-IV and eICU databases.
Peng S; Huang J; Liu X; Deng J; Sun C; Tang J; Chen H; Cao W; Wang W; Duan X; Luo X; Peng S
Front Cardiovasc Med; 2022; 9():994359. PubMed ID: 36312291
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. The prediction of in-hospital mortality in chronic kidney disease patients with coronary artery disease using machine learning models.
Ye Z; An S; Gao Y; Xie E; Zhao X; Guo Z; Li Y; Shen N; Ren J; Zheng J
Eur J Med Res; 2023 Jan; 28(1):33. PubMed ID: 36653875
[TBL] [Abstract][Full Text] [Related]
5. Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit.
Zou K; Huang S; Ren W; Xu H; Zhang W; Shi X; Shi L; Zhong X; Peng Y; Lü M; Tang X
Int J Gen Med; 2023; 16():2541-2553. PubMed ID: 37351008
[TBL] [Abstract][Full Text] [Related]
6. Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method.
Pan X; Xie J; Zhang L; Wang X; Zhang S; Zhuang Y; Lin X; Shi S; Shi S; Lin W
BMC Infect Dis; 2023 Feb; 23(1):76. PubMed ID: 36747139
[TBL] [Abstract][Full Text] [Related]
7. [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]
8. 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]
9. [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]
10. Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis.
Tang XW; Ren WS; Huang S; Zou K; Xu H; Shi XM; Zhang W; Shi L; Lü MH
World J Hepatol; 2024 Apr; 16(4):625-639. PubMed ID: 38689750
[TBL] [Abstract][Full Text] [Related]
11. Twenty-eight-day in-hospital mortality prediction for elderly patients with ischemic stroke in the intensive care unit: Interpretable machine learning models.
Huang J; Jin W; Duan X; Liu X; Shu T; Fu L; Deng J; Chen H; Liu G; Jiang Y; Liu Z
Front Public Health; 2022; 10():1086339. PubMed ID: 36711330
[TBL] [Abstract][Full Text] [Related]
12. A machine learning-based prediction model for in-hospital mortality among critically ill patients with hip fracture: An internal and external validated study.
Lei M; Han Z; Wang S; Han T; Fang S; Lin F; Huang T
Injury; 2023 Feb; 54(2):636-644. PubMed ID: 36414503
[TBL] [Abstract][Full Text] [Related]
13. A Novel Composite Indicator of Predicting Mortality Risk for Heart Failure Patients With Diabetes Admitted to Intensive Care Unit Based on Machine Learning.
Yang B; Zhu Y; Lu X; Shen C
Front Endocrinol (Lausanne); 2022; 13():917838. PubMed ID: 35846312
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.
Awad A; Bader-El-Den M; McNicholas J; Briggs J
Int J Med Inform; 2017 Dec; 108():185-195. PubMed ID: 29132626
[TBL] [Abstract][Full Text] [Related]
16. Development of a machine learning-based prediction model for sepsis-associated delirium in the intensive care unit.
Zhang Y; Hu J; Hua T; Zhang J; Zhang Z; Yang M
Sci Rep; 2023 Aug; 13(1):12697. PubMed ID: 37542106
[TBL] [Abstract][Full Text] [Related]
17. Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.
Kong G; Lin K; Hu Y
BMC Med Inform Decis Mak; 2020 Oct; 20(1):251. PubMed ID: 33008381
[TBL] [Abstract][Full Text] [Related]
18. Mortality prediction for patients with acute respiratory distress syndrome based on machine learning: a population-based study.
Huang B; Liang D; Zou R; Yu X; Dan G; Huang H; Liu H; Liu Y
Ann Transl Med; 2021 May; 9(9):794. PubMed ID: 34268407
[TBL] [Abstract][Full Text] [Related]
19. Construction and validation of machine learning models for sepsis prediction in patients with acute pancreatitis.
Liu F; Yao J; Liu C; Shou S
BMC Surg; 2023 Sep; 23(1):267. PubMed ID: 37658375
[TBL] [Abstract][Full Text] [Related]
20. Illness severity assessment of older adults in critical illness using machine learning (ELDER-ICU): an international multicentre study with subgroup bias evaluation.
Liu X; Hu P; Yeung W; Zhang Z; Ho V; Liu C; Dumontier C; Thoral PJ; Mao Z; Cao D; Mark RG; Zhang Z; Feng M; Li D; Celi LA
Lancet Digit Health; 2023 Oct; 5(10):e657-e667. PubMed ID: 37599147
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
