Targeted Chemotherapy with Personalized Immunotherapy (eBook)

An AI Approach

Abhishek Kumar, Prasenjit Das, Pramod Singh Rathore, Sachin Ahuja, Chetan Sharma (Herausgeber)

eBook Download: PDF

2025
536 Seiten
Wiley-Scrivener (Verlag)
978-1-394-27060-6 (ISBN)

Infos

Targeted Chemotherapy with Personalized Immunotherapy: An AI Approach is an essential guide for healthcare teams, offering groundbreaking insights into novel immunotherapies and personalized treatments to improve cancer patient care and quality of life.

In the last 20 years, there have been significant leaps forward in the treatment of cancer. We now have a far better understanding of how our cells interact with one another, how cancer suppresses and hides from the immune system, and how to support the body in reacting to stop the spread of cancer. Nevertheless, there is still a great deal more to learn in this field. Researchers are working to develop methods that will help pinpoint the most effective treatment for patients. Through this research, they have discovered that, for certain patients, the best results may be reached by combining precisely targeted chemotherapy with personalized immunotherapy.

Instead of treating patients with medications that are detrimental to the body as a whole, researchers now aim to identify the molecules that play an essential part in the communication that takes place between cells. This study will help pave the way for the development of novel immunotherapies that will help the body in its fight against cancer. In order to accurately plan cancer treatment, participation from a number of different members of the healthcare team is essential. This book is a comprehensive guide for all members of this team, providing insights into groundbreaking new treatments to cure more patients and improve quality of life.

Abhishek Kumar, PhD is an associate professor and Assistant Director in the Computer Science and Engineering Department at Chandigarh University with over 11 years of experience. He has over 100 publications in reputed, national and international journals, books, and conferences. His research interests include artificial intelligence, renewable energy image processing, computer vision, data mining, and machine learning.

Prasenjit Das, PhD is a professor in the Department of Computer Science and Engineering at Chandigarh University with over 19 years of experience. He has published two books, over 20 research papers, and 25 patents, three of which have been granted. His research interests include data mining, machine learning, image processing, and natural language processing.

Pramod Singh Rathore, PhD is an Assistant Professor in the Department of Computer and Communication Engineering at Manipal University Jaipur with over 12 years of teaching experience. He has published over 85 papers in peer-reviewed national and international journals, books, and conferences. His research interests include networking, image processing, and machine learning.

Sachin Ahuja, PhD has an illustrious academic and research career, marked by numerous impactful contributions. An accomplished editor, he has contributed to numerous high-quality academic books and served as a guest editor for special issues in reputed international journals, showcasing his expertise in emerging research domains. Additionally, he has successfully led several funded projects in advanced areas, including artificial intelligence, machine learning, and data mining, driving innovation and practical solutions.

Chetan Sharma is the Program Manager at the upGrad Campus for upGradEducation Private Limited. He has published one book, over 40 research articles in national and international journals and conferences, and 30 patents, eight of which have been granted. His research interests include natural language processing, machine learning, and management.

Produkt-Details

• Erscheint lt. Verlag: 29.8.2025
• Sprache: englisch
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete
• Themenwelt: Studium ► Querschnittsbereiche ► Infektiologie / Immunologie
• Schlagworte: AI in Cancer Analysis • AI in cancer detection • AI in Cancer Prognosis • AI in Multiomics Data Analysis • AI in Mutation Treatment Analysis • Bias in Cancer Data • Cancer Data Analysis • Cancer Genomic Data Analysis • Cancer Image Categorization • Cancer Image Research • Deep Learning in Cancer • Deep Learning in Cancer Detection • Deep Learning in Cancer Prognosis • Explainable AI • Fairness in Cancer Research
• ISBN-10: 1-394-27060-7 / 1394270607
• ISBN-13: 978-1-394-27060-6 / 9781394270606