Data Augmentation in Healthcare Data Modalities: A Comprehensive Review

Key Points

• The central aim is to evaluate the role and effectiveness of data augmentation in various healthcare data modalities.
• Conducted a comprehensive literature review to analyze different data augmentation techniques.
• Examined applications across various healthcare data types, including biomedical images and electronic health records.
• Discussed methodological approaches and their implications on improving data quality and model performance.
• Data augmentation significantly enhances model performance in healthcare applications.
• Various techniques have shown improved accuracy and robustness across different healthcare datasets.
• Findings suggest that data augmentation can address issues related to data scarcity in healthcare.