Diabetes is a complex disorder that can lead to numerous severe complications. Early diagnosis and treatment significantly contributes to a better quality of life for patients and can protect against associated complications. This chapter proposes the application of an Adaptive Neuro-fuzzy Inference System (ANFIS), with system parameters optimised by Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO). A comparative experimental study is conducted with application upon the UCI Early-Stage Diabetes Risk Prediction dataset, demonstrating effectiveness of the neuro-fuzzy system in diagnosing diabetes.
|Title of host publication||Artificial Intelligence in Healthcare|
|Subtitle of host publication||Recent Applications and Developments|
|Editors||Tianhua Chen, Jenny Carter, Mufti Mahmud, Arjab Singh Khuman|
|Number of pages||22|
|Publication status||Published - 26 Oct 2022|
|Name||Brain Informatics and Health|