June 2026
Intermediate
400 pages
10h 11m
English
book
Composite Artificial Intelligence
by T. S. Arun Samuel, L. Jerart Julus, P. Kanimozhi, T. Ananth Kumar, S. Balamurugan
Content preview from Composite Artificial Intelligence
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13Integrating Imaging and Genomic Data with Composite AI to Enhance Breast Cancer Diagnosis and Early Detection
P. Manju Bala1, S. Usharani2, A. Balachandar3, Sunday Adeola Ajagbe4* and Matthew Olusegun Adigun4
1Department of Artificial Intelligence and Data Science, IFET College of Engineering Villupram, Tamil Nadu, India
2Department of Artificial Intelligence and Machine Learning, IFET College of Engineering, Villupram, Tamil Nadu, India
3Department of Computer Science and Engineering, IFET College of Engineering Villupram, Tamil Nadu, India
4Department of Computer Science, University of Zululand, Kwadlangezwa, South Africa
Abstract
Early detection of breast cancer will increase patient outcomes and survival, which will aid in improved patient care. However, integrating genetic data with medical imaging will enhance our understanding of the condition, resulting in a more accurate diagnosis and tailored therapy for the patient. Multiple artificial intelligence techniques coupled to create composite AI can enhance the interpretation of the aggregated data and pave the way for new, cutting-edge research directions in breast cancer. In this study, we present an integrated artificial intelligence system that improves breast cancer detection by combining data from genomics and imaging techniques. Our solution is a hybrid strategy that employs CNN models for image data and machine learning models (SVMs and Random Forests) for processing genomic data. We employ stacking, an additional ...
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