是时候让机器学习算法来预测慢性肾病患者的肾衰竭风险了吗？
Is It Time for Machine Learning Algorithms to Predict the Risk of Kidney Failure in Patients with Chronic Kidney Disease?
作者信息
Thongprayoon Charat, Kaewput Wisit, Choudhury Avishek, Hansrivijit Panupong, Mao Michael A, Cheungpasitporn Wisit
机构信息
Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand.
出版信息
J Clin Med. 2021 Mar 8;10(5):1121. doi: 10.3390/jcm10051121.
Abstract
Chronic kidney disease (CKD) is a common clinical problem affecting more than 800 million people with different kidney diseases [...].
摘要
慢性肾脏病（CKD）是一个常见的临床问题，影响着超过8亿患有不同肾脏疾病的人群[……]。
相似文献
1
Is It Time for Machine Learning Algorithms to Predict the Risk of Kidney Failure in Patients with Chronic Kidney Disease?
J Clin Med. 2021 Mar 8;10(5):1121. doi: 10.3390/jcm10051121.
2
Neural network and support vector machine for the prediction of chronic kidney disease: A comparative study.
Comput Biol Med. 2019 Jun;109:101-111. doi: 10.1016/j.compbiomed.2019.04.017. Epub 2019 Apr 25.
3
Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy.
Crit Care. 2020 Feb 6;24(1):42. doi: 10.1186/s13054-020-2752-7.
4
Machine learning in nephrology: scratching the surface.
Chin Med J (Engl). 2020 Mar 20;133(6):687-698. doi: 10.1097/CM9.0000000000000694.
5
Clinical risk assessment of patients with chronic kidney disease by using clinical data and multivariate models.
Int Urol Nephrol. 2016 Dec;48(12):2069-2075. doi: 10.1007/s11255-016-1346-4. Epub 2016 Jun 22.
6
Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.
PLoS One. 2020 Sep 17;15(9):e0239262. doi: 10.1371/journal.pone.0239262. eCollection 2020.
7
Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases.
Int J Mol Sci. 2020 Jul 7;21(13):4802. doi: 10.3390/ijms21134802.
8
Optimized Identification of Advanced Chronic Kidney Disease and Absence of Kidney Disease by Combining Different Electronic Health Data Resources and by Applying Machine Learning Strategies.
J Clin Med. 2020 Sep 12;9(9):2955. doi: 10.3390/jcm9092955.
9
Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.
Int J Med Inform. 2019 Oct;130:103957. doi: 10.1016/j.ijmedinf.2019.103957. Epub 2019 Aug 24.
10
Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data.
J Med Internet Res. 2019 Feb 15;21(2):e11757. doi: 10.2196/11757.
引用本文的文献
1
Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.
Ren Fail. 2025 Dec;47(1):2489715. doi: 10.1080/0886022X.2025.2489715. Epub 2025 Apr 15.
2
A Klotho-Based Machine Learning Model for Prediction of both Kidney and Cardiovascular Outcomes in Chronic Kidney Disease.
Kidney Dis (Basel). 2024 Mar 25;10(3):200-212. doi: 10.1159/000538510. eCollection 2024 Jun.
3
Characteristics of Kidney Transplant Recipients with Prolonged Pre-Transplant Dialysis Duration as Identified by Machine Learning Consensus Clustering: Pathway to Personalized Care.
J Pers Med. 2023 Aug 19;13(8):1273. doi: 10.3390/jpm13081273.
4
Revolutionizing Chronic Kidney Disease Management with Machine Learning and Artificial Intelligence.
J Clin Med. 2023 Apr 21;12(8):3018. doi: 10.3390/jcm12083018.
5
Early Detection and Diagnosis of Chronic Kidney Disease Based on Selected Predominant Features.
J Healthc Eng. 2023 Jan 30;2023:3553216. doi: 10.1155/2023/3553216. eCollection 2023.
6
Explainable Preoperative Automated Machine Learning Prediction Model for Cardiac Surgery-Associated Acute Kidney Injury.
J Clin Med. 2022 Oct 24;11(21):6264. doi: 10.3390/jcm11216264.
7
Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering.
Med Sci (Basel). 2021 Sep 24;9(4):60. doi: 10.3390/medsci9040060.
8
Subtyping Hyperchloremia among Hospitalized Patients by Machine Learning Consensus Clustering.
Medicina (Kaunas). 2021 Aug 30;57(9):903. doi: 10.3390/medicina57090903.
本文引用的文献
1
Subtyping CKD Patients by Consensus Clustering: The Chronic Renal Insufficiency Cohort (CRIC) Study.
J Am Soc Nephrol. 2021 Mar;32(3):639-653. doi: 10.1681/ASN.2020030239. Epub 2021 Jan 18.
2
The Kidney Failure Risk Equation for Prediction of Allograft Loss in Kidney Transplant Recipients.
Kidney Med. 2020 Oct 28;2(6):753-761.e1. doi: 10.1016/j.xkme.2020.09.004. eCollection 2020 Nov-Dec.
3
Contemporary National Outcomes of Acute Myocardial Infarction-Cardiogenic Shock in Patients with Prior Chronic Kidney Disease and End-Stage Renal Disease.
J Clin Med. 2020 Nov 18;9(11):3702. doi: 10.3390/jcm9113702.
4
Performance of the Kidney Failure Risk Equation by Disease Etiology in Advanced CKD.
Clin J Am Soc Nephrol. 2020 Oct 7;15(10):1424-1432. doi: 10.2215/CJN.03940320. Epub 2020 Sep 14.
5
Remission of Proteinuria May Protect against Progression to Chronic Kidney Disease in Pediatric-Onset IgA Nephropathy.
J Clin Med. 2020 Jun 30;9(7):2058. doi: 10.3390/jcm9072058.
6
Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation.
J Clin Med. 2020 Apr 13;9(4):1107. doi: 10.3390/jcm9041107.
7
Prediction of Progression in Polycystic Kidney Disease Using the Kidney Failure Risk Equation and Ultrasound Parameters.
Can J Kidney Health Dis. 2020 Mar 18;7:2054358120911274. doi: 10.1177/2054358120911274. eCollection 2020.
8
Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine.
Database (Oxford). 2020 Jan 1;2020. doi: 10.1093/database/baaa010.
9
The Kidney Failure Risk Equation for prediction of end stage renal disease in UK primary care: An external validation and clinical impact projection cohort study.
PLoS Med. 2019 Nov 6;16(11):e1002955. doi: 10.1371/journal.pmed.1002955. eCollection 2019 Nov.
10
The Effect of Health-Related Behaviors on Disease Progression and Mortality in Early Stages of Chronic Kidney Disease: A Korean Nationwide Population-Based Study.
J Clin Med. 2019 Jul 25;8(8):1100. doi: 10.3390/jcm8081100.
Zotero 插件