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Full Description
Artificial Intelligence-Driven Precision Medicine for Triple-Negative Breast Cancer: Innovations and Insights in TNBC Management is a groundbreaking exploration into the transformative role of artificial intelligence in revolutionizing the management of triple-negative breast cancer (TNBC). In 19 chapters, this comprehensive guide navigates the intersection of cutting-edge technology and healthcare, offering insights that bridge the gap among medical professionals, researchers, and individuals affected by TNBC. Diving into the complexities of TNBC, this book unveils the potential of artificial intelligence (AI) in enhancing diagnostic accuracy, personalizing treatment strategies, and reshaping the landscape of breast cancer care. From radiomics and genomic data analysis to predictive modeling and patient engagement, each chapter unveils the latest innovations and provides the practical applications of AI to empower healthcare practitioners and improve patient outcomes. This book is a timely and valuable resource for health professionals, scientists and researchers, students, and all those who wish to broaden their knowledge in the allied field.
Contents
Section I: Foundations of Artificial Intelligence in Triple Negative Breast Cancer (TNBC)
1. Introduction to Triple Negative Breast Cancer and Precision Medicine
2. Understanding the Molecular Landscape of Triple Negative Breast Cancer
3. Challenges in Traditional TNBC Therapies
4. Fundamentals of Artificial Intelligence in Healthcare
5. The Intersection of AI and Oncology: A Comprehensive Overview
6. Managing Big Data for TNBC Research
Section II: Applications and Innovations in AI-Driven Precision Medicine for TNBC
7. Enhancing Early Detection and Diagnosis using AI Technologies
8. Predictive Modeling for Treatment Response in TNBC
9. AI Driven Biomarker Discovery and Validation
10. Precision Treatment Planning and Decision Support Systems
11. AI in Targeted Drug Discovery for TNBC
12. Integrating Multi-Omics Data for Personalized TNBC Management
13. Transforming Clinical Trials with AI Integration in TNBC Research
14. Ethical and Regulatory Dimensions of AI in TNBC Management
15. AI-Driven Approaches for Cancer Recurrence Monitoring
16. Advancements in Immunotherapy through AI-driven Approaches
17. AI-Driven Prognostic and Predictive Modeling in TNBC
18. Emerging Technologies for TNBC Management
