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This book describes the latest findings related to tumor molecular microenvironment and its involvement in cancer progression. It includes authoritative articles on recent progress in the field based on the current results of apoptosis, autophagy, and tumor signaling highlight new cancer targets for therapeutic manipulation as a strategy of cancer control. It explores the advancements of molecular mechanisms in oncology to identify new therapeutic, prognostic, and diagnostic targets in the molecular events of neoplasia. Recent data on nanoformulations in the book for the therapeutic management of various types of cancer indicate a revolutionary change in cancer therapy in the near future. The primary audience of this book is students and faculties from academic institutions, the researchers, scientists, clinicians, and scientists belong to the research and development wing in industries, as the book provides the latest data and findings in the described areas as a valuable source of incredible information in the field in an organized manner.
This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electri...
Vols. for 1964- have guides and journal lists.
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