238 related articles for article (PubMed ID: 38445452)
1. Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study.
Sun R; Li S; Wei Y; Hu L; Xu Q; Zhan G; Yan X; He Y; Wang Y; Li X; Luo A; Zhou Z
Int J Surg; 2024 May; 110(5):2950-2962. PubMed ID: 38445452
[TBL] [Abstract][Full Text] [Related]
2. Machine Learning-Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study.
Luo XQ; Kang YX; Duan SB; Yan P; Song GB; Zhang NY; Yang SK; Li JX; Zhang H
J Med Internet Res; 2023 Jan; 25():e41142. PubMed ID: 36603200
[TBL] [Abstract][Full Text] [Related]
3. Prediction of the development of acute kidney injury following cardiac surgery by machine learning.
Tseng PY; Chen YT; Wang CH; Chiu KM; Peng YS; Hsu SP; Chen KL; Yang CY; Lee OK
Crit Care; 2020 Jul; 24(1):478. PubMed ID: 32736589
[TBL] [Abstract][Full Text] [Related]
4. Risk Stratification for Postoperative Acute Kidney Injury in Major Noncardiac Surgery Using Preoperative and Intraoperative Data.
Lei VJ; Luong T; Shan E; Chen X; Neuman MD; Eneanya ND; Polsky DE; Volpp KG; Fleisher LA; Holmes JH; Navathe AS
JAMA Netw Open; 2019 Dec; 2(12):e1916921. PubMed ID: 31808922
[TBL] [Abstract][Full Text] [Related]
5. Interpretable machine learning models for early prediction of acute kidney injury after cardiac surgery.
Jiang J; Liu X; Cheng Z; Liu Q; Xing W
BMC Nephrol; 2023 Nov; 24(1):326. PubMed ID: 37936067
[TBL] [Abstract][Full Text] [Related]
6. Incorporating intraoperative blood pressure time-series variables to assist in prediction of acute kidney injury after type a acute aortic dissection repair: an interpretable machine learning model.
Dai A; Zhou Z; Jiang F; Guo Y; Asante DO; Feng Y; Huang K; Chen C; Shi H; Si Y; Zou J
Ann Med; 2023; 55(2):2266458. PubMed ID: 37813109
[TBL] [Abstract][Full Text] [Related]
7. Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications.
Xue B; Li D; Lu C; King CR; Wildes T; Avidan MS; Kannampallil T; Abraham J
JAMA Netw Open; 2021 Mar; 4(3):e212240. PubMed ID: 33783520
[TBL] [Abstract][Full Text] [Related]
8. An interpretable machine learning model to predict off-pump coronary artery bypass grafting-associated acute kidney injury.
Zeng Z; Tian X; Li L; Diao Y; Zhang T
Adv Clin Exp Med; 2024 May; 33(5):473-481. PubMed ID: 37593773
[TBL] [Abstract][Full Text] [Related]
9. Prediction of Acute Kidney Injury after Extracorporeal Cardiac Surgery (CSA-AKI) by Machine Learning Algorithms.
Tong Y; Niu X; Liu F
Heart Surg Forum; 2023 Oct; 26(5):E537-E551. PubMed ID: 37920093
[TBL] [Abstract][Full Text] [Related]
10. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.
Huang C; Murugiah K; Mahajan S; Li SX; Dhruva SS; Haimovich JS; Wang Y; Schulz WL; Testani JM; Wilson FP; Mena CI; Masoudi FA; Rumsfeld JS; Spertus JA; Mortazavi BJ; Krumholz HM
PLoS Med; 2018 Nov; 15(11):e1002703. PubMed ID: 30481186
[TBL] [Abstract][Full Text] [Related]
11. A web-based machine-learning algorithm predicting postoperative acute kidney injury after total knee arthroplasty.
Ko S; Jo C; Chang CB; Lee YS; Moon YW; Youm JW; Han HS; Lee MC; Lee H; Ro DH
Knee Surg Sports Traumatol Arthrosc; 2022 Feb; 30(2):545-554. PubMed ID: 32880677
[TBL] [Abstract][Full Text] [Related]
12. External Validation of a Prediction Model for Acute Kidney Injury Following Noncardiac Surgery.
Nishimoto M; Murashima M; Kokubu M; Matsui M; Eriguchi M; Samejima KI; Akai Y; Tsuruya K
JAMA Netw Open; 2021 Oct; 4(10):e2127362. PubMed ID: 34661665
[TBL] [Abstract][Full Text] [Related]
13. Preoperative plasma growth-differentiation factor-15 for prediction of acute kidney injury in patients undergoing cardiac surgery.
Heringlake M; Charitos EI; Erber K; Berggreen AE; Heinze H; Paarmann H
Crit Care; 2016 Oct; 20(1):317. PubMed ID: 27717384
[TBL] [Abstract][Full Text] [Related]
14. [Comparison of machine learning and Logistic regression model in predicting acute kidney injury after cardiac surgery: data analysis based on MIMIC-III database].
Xiong W; Zhang L; She K; Xu G; Bai S; Liu X
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2022 Nov; 34(11):1188-1193. PubMed ID: 36567564
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Application of Machine Learning Algorithms to Predict Acute Kidney Injury in Elderly Orthopedic Postoperative Patients.
Chen Q; Zhang Y; Zhang M; Li Z; Liu J
Clin Interv Aging; 2022; 17():317-330. PubMed ID: 35386749
[TBL] [Abstract][Full Text] [Related]
17. Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.
Hsu CN; Liu CL; Tain YL; Kuo CY; Lin YC
J Med Internet Res; 2020 Aug; 22(8):e16903. PubMed ID: 32749223
[TBL] [Abstract][Full Text] [Related]
18. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
[TBL] [Abstract][Full Text] [Related]
19. Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?
El-Galaly A; Grazal C; Kappel A; Nielsen PT; Jensen SL; Forsberg JA
Clin Orthop Relat Res; 2020 Sep; 478(9):2088-2101. PubMed ID: 32667760
[TBL] [Abstract][Full Text] [Related]
20. Prediction of acute kidney injury after cardiac surgery: model development using a Chinese electronic health record dataset.
Zhang H; Wang Z; Tang Y; Chen X; You D; Wu Y; Yu M; Chen W; Zhao Y; Chen X
J Transl Med; 2022 Apr; 20(1):166. PubMed ID: 35397573
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]