Search results for ""Author Rishabha Malviya""

MULTI-DRUG RESISTANCE IN CANCER The book details the mechanisms underlying multi-drug cellular resistance and the targets of novel chemotherapeutic agents. Cancer is a major killer all over the world. Even with all the progress made, chemotherapy is still the mainstay of modern cancer treatment. The progression of the cellular defeat of numerous independent anticancer drugs in terms of their chemical structure is a major barrier to successful chemotherapy. Multi-drug resistance (MDR) is a term for the fact that most cancer patients exhibit this phenomenon. According to the numbers, drug resistance carries the blame for 90% of cancer patient deaths. Refractory cancer and tumor recurrence are common outcomes of prolonged chemotherapy. Because of the prevalence of drug-resistance mutations, the difficulty of treating tumors increases and the therapeutic efficacy of drugs decreases. Multi-Drug Resistance in Cancer: Mechanism and Treatment Strategies contains nine chapters that cover topics such as: studying the mechanics of resistance to drugs by autophagy; studies to delineate the role of efflux transporters; expression of drug transporters; resistance to targeted therapies in breast cancer; advances in metallodrug driven combination treatment for cancer; and use of natural agents for the overcoming of cancer drug resistance. The book aims to provide the latest data on the mechanisms of cellular resistance to anticancer agents currently used in clinical treatment. It provides a better understanding of the mechanisms of MDR and targets of novel chemotherapy agents which should guide future research concerning new effective strategies in cancer treatment. Audience This book is written for pharmaceutical and biomedical scientists and researchers at both the bench and in the clinic who are interested in the mechanisms and strategies for overcoming cancer’s multi-drug resistance.

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ARTIFICIAL INTELLIGENCE FOR BONE DISORDER The authors have produced an invaluable resource that connects the fields of AI and bone treatment by providing essential insights into the current state and future of AI in bone condition diagnosis and therapy, as well as a methodical examination of machine learning algorithms, deep learning approaches, and their real-world uses. The book explores the use of artificial intelligence (AI) in the diagnosis and treatment of various bone illnesses. The integration of AI approaches in the fields of orthopedics, radiography, tissue engineering, and other areas related to bone are discussed in detail. It covers tissue engineering methods for bone regeneration and investigates the use of AI tools in this area, emphasizing the value of deep learning and how to use AI in tissue engineering efficiently. The book also covers diagnostic and prognostic uses of AI in orthopedics, such as the diagnosis of disorders involving the hip and knee as well as prognoses for therapies. Chapters also look at MRI, trabecular biomechanical strength, and other methods for diagnosing osteoporosis. Other issues the book examines include several uses of AI in pediatric orthopedics, 3D modeling, digital X-ray radiogrammetry, convolutional neural networks for customized care, and digital tomography. With information on the most recent developments and potential future applications, each chapter of the book advances our understanding of how AI might be used to diagnose and treat bone problems. Audience This book will serve as a guide for orthopedic experts, biomedical engineers, faculty members, research scholars, IT specialists, healthcare workers, and hospital administrators.

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HUMAN-MACHINE INTERFACE The book contains the latest advances in healthcare and presents them in the frame of the Human-Machine Interface (HMI). The Human-Machine Interface (HMI) industry has witnessed the evolution from a simple push button to a modern touch-screen display. HMI is a user interface that allows humans to operate controllers for machines, systems, or instruments. Most medical procedures are improved by HMI systems, from calling an ambulance to ensuring that a patient receives adequate treatment on time. This book describes the scenario of biomedical technologies in the context of the advanced HMI, with a focus on direct brain-computer connection. The book describes several HMI tools and related techniques for analyzing, creating, controlling, and upgrading healthcare delivery systems, and provides details regarding how advancements in technology, particularly HMI, ensure ethical and fair use in patient care. Audience The target audience for this book is medical personnel and policymakers in healthcare and pharmaceutical professionals, as well as engineers and researchers in computer science and artificial intelligence.

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DEEP LEARNING FOR TREATMENTS The book provides the direction for future research in deep learning in terms of its role in targeted treatment, biological systems, site-specific drug delivery, risk assessment in therapy, etc. Deep Learning for Targeted Treatments describes the importance of the deep learning framework for patient care, disease imaging/detection, and health management. Since deep learning can and does play a major role in a patient’s healthcare management by controlling drug delivery to targeted tissues or organs, the main focus of the book is to leverage the various prospects of the DL framework for targeted therapy of various diseases. In terms of its industrial significance, this general-purpose automatic learning procedure is being widely implemented in pharmaceutical healthcare. Audience The book will be immensely interesting and useful to researchers and those working in the areas of clinical research, disease management, pharmaceuticals, R&D formulation, deep learning analytics, remote healthcare management, healthcare analytics, and deep learning in the healthcare industry.

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