174 related articles for article (PubMed ID: 37950672)
1. Using machine learning algorithms to predict 28-day mortality in critically ill elderly patients with colorectal cancer.
Guo C; Pan J; Tian S; Gao Y
J Int Med Res; 2023 Nov; 51(11):3000605231198725. PubMed ID: 37950672
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
5. 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]
6. 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]
7. [Prediction of intensive care unit readmission for critically ill patients based on ensemble learning].
Lin Y; Wu JY; Lin K; Hu YH; Kong GL
Beijing Da Xue Xue Bao Yi Xue Ban; 2021 Jun; 53(3):566-572. PubMed ID: 34145862
[TBL] [Abstract][Full Text] [Related]
8. Real-time machine learning model to predict short-term mortality in critically ill patients: development and international validation.
Lim L; Gim U; Cho K; Yoo D; Ryu HG; Lee HC
Crit Care; 2024 Mar; 28(1):76. PubMed ID: 38486247
[TBL] [Abstract][Full Text] [Related]
9. A time-incorporated SOFA score-based machine learning model for predicting mortality in critically ill patients: A multicenter, real-world study.
Liu Y; Gao K; Deng H; Ling T; Lin J; Yu X; Bo X; Zhou J; Gao L; Wang P; Hu J; Zhang J; Tong Z; Liu Y; Shi Y; Ke L; Gao Y; Li W
Int J Med Inform; 2022 Jul; 163():104776. PubMed ID: 35512625
[TBL] [Abstract][Full Text] [Related]
10. Identification of key predictors of hospital mortality in critically ill patients with embolic stroke using machine learning.
Liu W; Ma W; Bai N; Li C; Liu K; Yang J; Zhang S; Zhu K; Zhou Q; Liu H; Guo J; Li L
Biosci Rep; 2022 Sep; 42(9):. PubMed ID: 35993194
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. 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]
13. INTERPRETABLE MACHINE LEARNING FOR PREDICTING RISK OF INVASIVE FUNGAL INFECTION IN CRITICALLY ILL PATIENTS IN THE INTENSIVE CARE UNIT: A RETROSPECTIVE COHORT STUDY BASED ON MIMIC-IV DATABASE.
Cao Y; Li Y; Wang M; Wang L; Fang Y; Wu Y; Liu Y; Liu Y; Hao Z; Kang H; Gao H
Shock; 2024 Jun; 61(6):817-827. PubMed ID: 38407989
[TBL] [Abstract][Full Text] [Related]
14. Interpretable machine learning models for predicting 90-day death in patients in the intensive care unit with epilepsy.
She Y; Zhou L; Li Y
Seizure; 2024 Jan; 114():23-32. PubMed ID: 38035490
[TBL] [Abstract][Full Text] [Related]
15. Novel pneumonia score based on a machine learning model for predicting mortality in pneumonia patients on admission to the intensive care unit.
Wang B; Li Y; Tian Y; Ju C; Xu X; Pei S
Respir Med; 2023 Oct; 217():107363. PubMed ID: 37451647
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Interpretable machine learning models for predicting venous thromboembolism in the intensive care unit: an analysis based on data from 207 centers.
Guan C; Ma F; Chang S; Zhang J
Crit Care; 2023 Oct; 27(1):406. PubMed ID: 37875995
[TBL] [Abstract][Full Text] [Related]
18. Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers.
Zhang G; Shao F; Yuan W; Wu J; Qi X; Gao J; Shao R; Tang Z; Wang T
Eur J Med Res; 2024 Mar; 29(1):156. PubMed ID: 38448999
[TBL] [Abstract][Full Text] [Related]
19. Construction and validation of prognostic models in critically Ill patients with sepsis-associated acute kidney injury: interpretable machine learning approach.
Fan Z; Jiang J; Xiao C; Chen Y; Xia Q; Wang J; Fang M; Wu Z; Chen F
J Transl Med; 2023 Jun; 21(1):406. PubMed ID: 37349774
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
