An Optimisation-Driven Prediction Method for Automated Diagnosis and Prognosis
This article presents a novel hybrid classification paradigm for medical diagnoses and prognoses prediction. The core mechanism of the proposed method relies on a centroid classification algorithm whose logic is exploited to formulate the classification task as a real-valued optimisation problem. A novel metaheuristic combining the algorithmic structure of Swarm Intelligence optimisers with the probabilistic search models of Estimation of Distribution Algorithms is designed to optimise such a problem, thus leading to high-accuracy predictions. This method is tested over 11 medical datasets and compared against 14 cherry-picked classification algorithms. Results show that the proposed approach is competitive and superior to the state-of-the-art on several occasions.
open access article
Citation : Santucci, V., Milani, A., Caraffini, F. (2019) An Optimisation-Driven Prediction Method for Automated Diagnosis and Prognosis. Mathematics, 7, 1051.
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes