Diagnosis of vertebral column pathologies using concatenated resampling with machine learning algorithms.

ABSTRACT: Medical diagnosis through the classification of biomedical attributes is one of the exponentially growing fields in bioinformatics. Although a large number of approaches have been presented in the past, wide use and superior performance of the machine learning (ML) methods in medical diagnosis necessitates significant consideration for automatic diagnostic methods. This study proposes a novel approach called concatenated resampling (CR) to increase the efficacy of traditional ML algorithms. The performance is analyzed leveraging four ML approaches like tree-based ensemble approaches, and linear machine learning approach for automatic diagnosis of inter-vertebral pathologies with increased. Besides, undersampling, over-sampling, and proposed CR techniques have been applied to unbalanced tra

SUBMITTER: Reshi AA 

PROVIDER: S-EPMC8323723 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature