A self-inspected adaptive SMOTE algorithm (SASMOTE) for highly imbalanced data classification in healthcare
Work
Year: 2023
Type: article
Abstract: In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Tec... more
Source: BioData Mining
Institutions University of Houston, Oklahoma State University, Johns Hopkins Medicine, Johns Hopkins University
Cites: 25
Cited by: 33
Related to: 10
FWCI: 8.824
Citation percentile (by year/subfield): 100
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
APC paid (est): $2,072
Grant ID R01MH121394