Adaptive Kernel Probability Model (AKPM) for Interpretable and Reliable Diabetes Prediction using Clinical Diagnostic Data

Today's article comes from the journal of Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC). The authors are Hiswati et al., from the Universitas Respati Yogyakarta, in Indonesia. In this paper they propose a new model for diabetes prediction: it's a nonparametric probabilistic classifier that estimates class-conditional probability densities using adaptive kernel density estimation.

DOI: 10.28989/avitec.v8i1.3689