Prognostic prediction of idiopathic membranous nephropathy using interpretable machine learning.

Background: Established prognostic models of idiopathic membranous nephropathy (IMN) were limited to traditional modeling methods and did not comprehensively consider clinical and pathological patient data. Based on the electronic medical record (EMR) system, machine learning (ML) was used to construct a risk prediction model for the prognosis of IMN.

Methods: Data from 418 patients with IMN were diagnosed by renal biopsy at the Fifth Clinical Medical College of Shanxi Medical University.

Boosting the Utilization and Electrochemical Performances of Polyaniline by Forming a Binder-Free Nanoscale Coaxially Coated Polyaniline/Carbon Nanotube/Carbon Fiber Paper Hierarchical 3D Microstructure Composite as a Supercapacitor Electrode.

Nanoscale polyaniline (PANI) is formed on a hierarchical 3D microstructure carbon nanotubes (CNTs)/carbon fiber paper (CFP) substrate a one-step electrochemical polymerization method. The chemical and structural properties of the binder-free PANI/CNTs/CFP electrode are characterized by field emission scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy. The specific capacitance of PANI/CNTs/CFP tested in a symmetric two-electrode system reaches 731.