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This book explores a wide range of methods for advanced solutions in the field of oncology. It explores the transformative role of AI in advancing cancer care, focusing on its applications in drug discovery, surgical progress, and digital twin technology. The book provides an in-depth analysis of AI's impact on various cancers, including breast, colorectal, brain, and others, and highlights its potential to enhance early detection, accurate diagnosis, and personalized treatment. The book will investigate the development and optimization of AI algorithms to achieve high accuracy in detecting malignant cells at different stages. The technologies encompass machine learning techniques to identify patterns in medical imaging, natural language processing to evaluate patient histories, and deep learning models to forecast treatment outcomes. Specific methodologies such as supervised and unsupervised learning models, convolutional neural networks for image analysis, and reinforcement learning for adaptive treatment strategies are provided. The utilization of case studies and real-world examples in cancer care will demonstrate every approach, enabling readers to gain a practical understanding of how these technologies might be implemented.
This book explores a wide range of methods for advanced solutions in the field of oncology. It explores the transformative role of AI in advancing cancer care, focusing on its applications in drug discovery, surgical progress, and digital twin technology. The book provides an in-depth analysis of AI's impact on various cancers, including breast, colorectal, brain, and others, and highlights its potential to enhance early detection, accurate diagnosis, and personalized treatment. The book will investigate the development and optimization of AI algorithms to achieve high accuracy in detecting malignant cells at different stages. The technologies encompass machine learning techniques to identify patterns in medical imaging, natural language processing to evaluate patient histories, and deep learning models to forecast treatment outcomes. Specific methodologies such as supervised and unsupervised learning models, convolutional neural networks for image analysis, and reinforcement learning for adaptive treatment strategies are provided. The utilization of case studies and real-world examples in cancer care will demonstrate every approach, enabling readers to gain a practical understanding of how these technologies might be implemented.
Dr. Rishabha Malviya completed B. Pharmacy from Uttar Pradesh Technical University and M. Pharmacy (Pharmaceutics) from Gautam Buddha Technical University, Lucknow Uttar Pradesh. His PhD (Pharmacy) work was in the area of Novel formulation development techniques. He has 12 years of research experience and presently working as Associate Professor in the Department of Pharmacy, School of Medical and Allied Sciences, Galgotias University since past 8 years. His area of interest includes formulation optimization, nanoformulation, targeted drug delivery, localized drug delivery and characterization of natural polymers as pharmaceutical excipients. He has authored more than 150 research/review papers for national/international journals of repute. He has 58 patents (19 grants, 38 published, 1 filed) and publications in reputed National and International journals with total of 250 cumulative impact factor. He has also received an Outstanding Reviewer award from Elsevier. He has authored/edited/editing 58 books (Wily, CRC Press/Taylor and Francis, Springer, River Publisher, IOP publishing and OMICS publication) and authored 50 book chapters. His name has included in word's top 2% scientist list for the year 2020, 2021 and 2022 by Elsevier BV and Stanford University. He is Reviewer/Editor/Editorial board member of more than 50 national and international journals of repute. He has invited as author for "Atlas of Science" and pharma magazine dealing with industry (B2B) "Ingredient south Asia Magazines".
Shivam Rajput completed B. Pharmacy from Pt. B. D. Sharma University of Health Sciences, Rohtak, and M. Pharmacy from Galgotias University, Greater Noida. He has authored two books with Scrivener Publishing/Wiley and Apple Academic Press/Taylor and Francis Group and one book is in press with Scrivener publishing/ Wiley. He has published more than 10 SCI/Scopus index papers with reputed publisher like Elsevier, Wiley and Bentham Science. He has attended more than 10 international conferences.
Dr. Mukesh Roy obtained his Doctor of Philosophy in Mechanical Engineering from South Dakota State University, USA, in 2021. His research endeavors concentrated on the study of the mechanics of vascular tissue to employ it as a template for engineering design and flexible biocomposites. After completing his Ph.D., Dr. Roy went on to complete a Postdoctoral Fellowship at the National Science Foundation's Engineering Research Center for Cellular Metamaterials (CELL-MET), Florida International University, USA in the year 2023. During this fellowship, Dr. Roy worked on the characterization of stem cell-laden cardiovascular patches, specifically focusing on myocardial tissue at multiple scales. Currently, Dr. Roy serves as a Clinical Researcher and Biostatistician at the Office of Clinical Research in Baptist Health South Florida-Miami, USA. Dr. Roy has a research experience of 8+ years and has authored and published over 24 peer-reviewed scientific articles, conference papers, 2 book chapters, and 40+ abstracts. In addition, Dr. Roy has filed 6 patents, with one granted in the USA and 5 published in India. Dr. Roy has received 6 awards and 3 fellowships for his research, creativity, and innovations. Furthermore, Dr. Roy serves as an editorial board member and reviewer for various journals and conferences in biomaterials, computational biomechanics, biomedical devices, and public health research.
Dr. Sathvik is currently working as an Associate Dean and Professor at RAK College of Pharmacy (RAKCOP), RAK Medical and Health Sciences University located in Ras Al Khaimah, United Arab Emirates. Dr. Sathvik has completed his Ph.D. in Clinical Pharmacy from Rajiv Gandhi University of Health Sciences, Bangalore, India. He has received an FIP fellowship for higher training in renal clinical pharmacy at Royal Adelaide Hospital and Queen Eli
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