172 related articles for article (PubMed ID: 38728685)
1. Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study.
Xie P; Wang H; Xiao J; Xu F; Liu J; Chen Z; Zhao W; Hou S; Wu D; Ma Y; Xiao J
J Med Internet Res; 2024 May; 26():e49848. PubMed ID: 38728685
[TBL] [Abstract][Full Text] [Related]
2. Improving the Prognostic Evaluation Precision of Hospital Outcomes for Heart Failure Using Admission Notes and Clinical Tabular Data: Multimodal Deep Learning Model.
Gao Z; Liu X; Kang Y; Hu P; Zhang X; Yan W; Yan M; Yu P; Zhang Q; Xiao W; Zhang Z
J Med Internet Res; 2024 May; 26():e54363. PubMed ID: 38696251
[TBL] [Abstract][Full Text] [Related]
3. Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.
Thorsen-Meyer HC; Nielsen AB; Nielsen AP; Kaas-Hansen BS; Toft P; Schierbeck J; Strøm T; Chmura PJ; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Belling K; Brunak S; Perner A
Lancet Digit Health; 2020 Apr; 2(4):e179-e191. PubMed ID: 33328078
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Machine learning in the prediction of in-hospital mortality in patients with first acute myocardial infarction.
Zhu X; Xie B; Chen Y; Zeng H; Hu J
Clin Chim Acta; 2024 Feb; 554():117776. PubMed ID: 38216028
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. Predicting acute kidney injury risk in acute myocardial infarction patients: An artificial intelligence model using medical information mart for intensive care databases.
Cai D; Xiao T; Zou A; Mao L; Chi B; Wang Y; Wang Q; Ji Y; Sun L
Front Cardiovasc Med; 2022; 9():964894. PubMed ID: 36158815
[TBL] [Abstract][Full Text] [Related]
9. Deep-learning-based risk stratification for mortality of patients with acute myocardial infarction.
Kwon JM; Jeon KH; Kim HM; Kim MJ; Lim S; Kim KH; Song PS; Park J; Choi RK; Oh BH
PLoS One; 2019; 14(10):e0224502. PubMed ID: 31671144
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Explainable Artificial Intelligence Warning Model Using an Ensemble Approach for In-Hospital Cardiac Arrest Prediction: Retrospective Cohort Study.
Kim YK; Koo JH; Lee SJ; Song HS; Lee M
J Med Internet Res; 2023 Dec; 25():e48244. PubMed ID: 38133922
[TBL] [Abstract][Full Text] [Related]
12. An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.
Huang D; Gong L; Wei C; Wang X; Liang Z
Respir Res; 2024 Jun; 25(1):246. PubMed ID: 38890628
[TBL] [Abstract][Full Text] [Related]
13. Machine Learning for Predicting Risk and Prognosis of Acute Kidney Disease in Critically Ill Elderly Patients During Hospitalization: Internet-Based and Interpretable Model Study.
Li M; Han S; Liang F; Hu C; Zhang B; Hou Q; Zhao S
J Med Internet Res; 2024 May; 26():e51354. PubMed ID: 38691403
[TBL] [Abstract][Full Text] [Related]
14. Development and validation of an artificial neural network algorithm to predict mortality and admission to hospital for heart failure after myocardial infarction: a nationwide population-based study.
Mohammad MA; Olesen KKW; Koul S; Gale CP; Rylance R; Jernberg T; Baron T; Spaak J; James S; Lindahl B; Maeng M; Erlinge D
Lancet Digit Health; 2022 Jan; 4(1):e37-e45. PubMed ID: 34952674
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Explainable Machine Learning Model for Predicting GI Bleed Mortality in the Intensive Care Unit.
Deshmukh F; Merchant SS
Am J Gastroenterol; 2020 Oct; 115(10):1657-1668. PubMed ID: 32341266
[TBL] [Abstract][Full Text] [Related]
17. Combining patient visual timelines with deep learning to predict mortality.
Mayampurath A; Sanchez-Pinto LN; Carey KA; Venable LR; Churpek M
PLoS One; 2019; 14(7):e0220640. PubMed ID: 31365580
[TBL] [Abstract][Full Text] [Related]
18. Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study.
Baek S; Jeong YJ; Kim YH; Kim JY; Kim JH; Kim EY; Lim JK; Kim J; Kim Z; Kim K; Chung MJ
J Med Internet Res; 2024 Jan; 26():e52134. PubMed ID: 38206673
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. 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]
[Next] [New Search]