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…mehr
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.
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
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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