Artificial Intelligence-Driven Precision Medicine for Triple Negative Breast Cancer

Artificial Intelligence-Driven Precision Medicine for Triple Negative Breast Cancer by Sachin Namdeo Kothawade and Vishal V. Pande offers a cutting-edge roadmap for clinicians, researchers, and healthcare leaders confronting one of oncology’s toughest challenges. Combining state-of-the-art AI methodologies with translational oncology, this book translates complex data into practical strategies to improve outcomes for patients with Triple Negative Breast Cancer (TNBC).

Begin with a compelling overview of how machine learning, deep learning, and multi-omics integration uncover actionable biomarkers and predict therapeutic response in TNBC. The authors distill advanced concepts—tumor heterogeneity, predictive modeling, computational pathology, and clinical decision support—into clear, clinically relevant guidance that bridges bench and bedside.

Designed for a global audience, the text highlights real-world applications across India, North America, Europe, and the Asia-Pacific region, making it especially valuable for oncology teams, bioinformaticians, and precision-medicine initiatives worldwide. Chapters emphasize reproducible workflows, model validation, and ethical considerations, empowering institutions to adopt AI-driven protocols while safeguarding patient data and equity.

Whether you are developing targeted therapies, designing clinical trials, or implementing AI pipelines in a hospital setting, this book equips you with practical tools and evidence-based insights to advance personalized care for TNBC patients. Scholarly yet accessible, it’s an essential reference for anyone committed to transforming cancer care with technology.

Secure your copy today and join the vanguard of precision oncology—gain the knowledge and confidence to harness artificial intelligence for better, more precise treatment of Triple Negative Breast Cancer.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.