Artificial Intelligence-Driven Precision Medicine for Triple Negative Breast Cancer : Innovations and Insights in TNBC Management

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Artificial Intelligence-Driven Precision Medicine for Triple Negative Breast Cancer : Innovations and Insights in TNBC Management

  • ウェブストア価格 ¥37,699(本体¥34,272)
  • Academic Press Inc(2025/10発売)
  • 外貨定価 US$ 175.00
  • 読書週間 ポイント2倍キャンペーン 対象商品(~11/9)
  • ポイント 684pt
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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 406 p.
  • 言語 ENG
  • 商品コード 9780443335655
  • DDC分類 616.99449

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

1. Introduction of triple negative breast cancer and precision medicine
Bhushan R. Rane, Rutuja R. Sawant, Pankaj V. Mhatre and Sachin N. Kothawade
2. Understanding the molecular landscape of triple-negative breast cancer
Ishrat Nazir, Ashish Garg, Sudarshan Singh and Sachin N. Kothawade
3. Challenges in traditional TNBC therapies
Somdatta Chaudhari, Aishwarya Pandit, Mukund Salunke, Shailaja Jadhav, Aarti Kulkarni and Sachin N. Kothawade
4. Fundamentals of artificial intelligence in healthcare
Punam B. Rane, Bhushan R. Rane, Sachin N. Kothawade and Puja P. Chaure
5. Artificial intelligence-driven precision medicine for triple negative breast cancer
Kuldeep Vinchurkar, Rohit Doke, Soham Joshi, Ganesh Muleva, Sudarshan Singh and Shradhanjali Singh
6. Managing big data for TNBC research
Sachin N. Kothawade, Sandesh S. Bole, Prashant B. Patil, Jayprakash S. Suryawanshi and Vishal V. Pande

Section II: Applications and innovations in AI-driven precision medicine for TNBC
7. Enhancing early detection and diagnosis using AI technologies in artificial intelligence- driven precision medicine for triple-negative breast cancer
Prashant Patil, Ganesh Sonawane, Kajal Pansare and Sachin N. Kothawade
8. Predictive modeling for treatment response in TNBC
Pooja V. Nagime, Sudarshan Singh and Sachin N. Kothawade
9. AI-driven biomarker discovery and validation
Kunal Ganesh Raut, Anuruddha R. Chabukswar, Swati C. Jagdale, Pooja T. Giri and Yuvraj Patil
10. Precision treatment planning and decision support systems
Prashant Tiwari, M Vijay Kumar, Sunil Kumar Kadiri, Sunny Rathee, Sakshi Soni and Debasis Sen
11. AI in targeted drug discovery for TNBC
Sachin N. Kothawade, Shreya Bhosale, Rutuja Jedhe, Priti Mhaske and Supriya Makhare
12. Integrating multiomics data for personalized TNBC management
Unmesh G. Bhamre, Harshal A. Kothawade, Deepali D. Bhandari, Sunil V. Amrutkar and Dattatraya M. Shinkar
13. Transforming clinical trials with AI integration in TNBC research
Sahebrao Boraste, Sakshi Wani and Deelip Derle
14. Ethical and regulatory dimensions of AI in TNBC management
Neha Minocha, Sunil Kumar Kadiri, Prashant Tiwari and Deepika Yadav
15. AI-driven approaches for cancer recurrence monitoring
Popat Mohite, Showkhiya Khan, Shubham Munde and Sayali Churi
16. Advancements in immunotherapy through AI-driven approaches
Popat Mohite, Gaurav Sawant, Ishlok Khadka, Dharam Gharat, Kavita Dwivedi and Sachin N. Kothawade
17. AI-driven prognostic and predictive modeling in triple-negative breast cancer (TNBC)
Prachi Parvatikar, Ifat Fatima Hatterkihal, Pankaj Kumar Singh, Vijaylaxmi Patil, S.V. Patil, Kuldeep Vinchurkar, Hardik Rana and Sachin N. Kothawade
18. Recent technologies for TNBC management
Poonam R. Inamdar, Ashwini R. Gawade, Parixit J. Bhandurge, Prajakta V. Adsule, Padmaja S. Kore and Sachin N. Kothawade

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