‎shannon entropy analysis of serum c-terminal agrin fragment as a biomarker for kidney function‎: ‎reference‎ ‎ranges‎, ‎healing sequences and insights

This article focuses on evaluating the success or failure of kidney transplantation using shannon entropy‎, ‎fuzzy sets‎, ‎and scaf‎. ‎the data for scaf references used in this study for both healthy individuals and kidney transplant recipients have been collected from the relevant literature‎. ‎for both groups‎, ‎scaf's shannon entropy values have been calculated using an appropriate probability density function and formulation‎, ‎and sequences have been generated for caf and scr biomarkers from entropy values‎, ‎with findings interpreted‎. ‎these sequences are called healing sequences‎. ‎a case study demonstrating whether the transplant procedure was successful or unsuccessful was presented using sequences that we refer to as healing sequences‎. ‎in this context‎, ‎the utilization of mathematical tools such as fuzzy sets‎, ‎shannon entropy‎, ‎and reference intervals becomes evident‎. ‎these tools provide a systematic and quantitative approach to assessing the outcomes of kidney transplantation‎. ‎by leveraging the principles of shannon entropy‎, ‎we gain insights into the degree of unpredictability and fuzziness associated with biomarker values‎, ‎which can be indicative of the transplant's success‎.‎furthermore‎, ‎the concept of healing sequences provides a valuable framework for tracking the progression of patients post-transplantation‎. ‎by monitoring changes in caf and scr biomarkers over time‎, ‎healthcare professionals can make informed decisions and interventions to ensure the well-being of kidney transplant recipients‎.