Discussion
tissue stiffness, CKD
RENAL FIBROSIS
A MLP model was developed in the present study based on 2D-SWE and easily accessible clinical features for noninvasive assessment of renal fibrosis in patients with CKD and further validated. This established model had favourable diagnostic performance, fine calibration, and satisfactory clinical value. To the best of our knowledge, this is the first study to apply the MLP network classifier integrating 2D-SWE to CKD patients. The presented MLP models could be an adjuvant decision-support system for medical treatment decision-making as well as routine follow-up assessment.As CKD progresses, different interventions for the various stages of renal fibrosis should be implemented to prevent exacerbation and improve prognosis [With an AUC of 0.93 in the training cohort and 0.86 in the test cohort, the constructed MLP model effectively differentiated patients with moderate-severe renal fibrosis from mild patients. This performance outperformed those obtained with the 2D-SWE modality alone [AUC = 0.76; 95% CI = 0.68 to 0.85] [Several classical ensemble machine learning models (such as eXtreme Gradient Boosting and random forest) were also applied to address relevant clinical issues [The diagnostic performance of the MLP model depends to the greatest extent upon the following features: first, the SWE value, followed by eGFR and age, then UACR, and finally renal RI. In SWE, tissue stiffness can be evaluated by examining the speed of propagation of shear waves generated as a result of deformation caused by acoustic radiation force impulses being applied to target tissue [The application of SWE for the evaluation of renal fibrosis has been the subject of previous investigations [There are still some limitations associated with this study. First, the sample size of this study was relatively small, especially in severe cases of renal fibrosis, and a larger population should be included for analysis in the future. Second, this was a single-center study, which could be further validated 