Nested genetic algorithm-based classifier selection and placement in multi-level ensemble framework for effective disease diagnosis.

• Tác giả: Srinivas Arukonda, Ramalingaswamy Cheruku
• Ngôn ngữ: eng
• Ký hiệu phân loại: 133.594 Types or schools of astrology originating in or associated with a
• Thông tin xuất bản: England : Computer methods in biomechanics and biomedical engineering , 2025
• Bộ sưu tập: NCBI
• ID: 250503

Tóm tắt

Effective disease diagnosis is a critical unmet need on a global scale. The intricacies of the numerous disease mechanisms and underlying symptoms make developing a model for early diagnosis and effective treatment extremely difficult. Machine learning (ML) can help to solve some of these issues. Recently, various ensemble-based ML models have benefited clinicians in early diagnosis. However, one of the most difficult challenges in multi-level ensemble approaches is the classifier selection and their placement in the ensemble framework as it improves the overall performance. Let