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Natural products have historically been key to drug discovery and therapeutic applications throughout many societies. In the modern era, natural bioactive compounds can be isolated, and their effects can be further studied for more successful outcomes. It is essential to study these natural bioactive compounds to enhance pharmaceuticals and drug discovery. Isolation, Characterization, and Therapeutic Applications of Natural Bioactive Compounds examines the applications of natural bioactive compounds from a health perspective. It discusses medicinal and therapeutic applications of natural bioactive molecules as well as the biological activities of different natural products and their properties. Covering topics such as drug discovery, government regulations, and phytochemical extraction, this premier reference source is an excellent resource for pharmacists, medical practitioners, phytologists, hospital administrators, government officials, faculty and students of higher education, librarians, researchers, and academicians.
This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing.
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Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicab...
Technological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signals observe physiological activities, which provide essential information to healthcare professionals. Biomedical signal processing can be optimized through artificial intelligence (AI) and machine learning (ML), presenting the next step towards smart healthcare. AI-Enabled Smart Healthcare Using Biomedical Signals will not only cover the mathematical description of the AI- and ML-based methods, but also analyze and demonstrate the usability of different AI methods f...
Recent advancements in the technology of medical imaging, such as CT and MRI scanners, are making it possible to create more detailed 3D and 4D images. These powerful images require vast amounts of digital data to help with the diagnosis of the patient. Artificial intelligence (AI) must play a vital role in supporting with the analysis of this medical imaging data, but it will only be viable as long as healthcare professionals and AI interact to embrace deep thinking platforms such as automation in the identification of diseases in patients. AI Innovation in Medical Imaging Diagnostics is an essential reference source that examines AI applications in medical imaging that can transform hospit...
Glial cells, including microglia, astrocytes, oligodendrocytes, and their progenitors NG2-glia, serve as key players in maintaining structural integrity and complex brain homeostasis. They actively participate in neurotransmission, energy metabolism, synaptic plasticity, neurogenesis, ion balance, immune defense, and the clearance of neuronal debris. However, the physiological functions of glial cells are often compromised in aging, neurodegenerative diseases such as Alzheimer's, Parkinson's, ALS, and multiple sclerosis, as well as in gliomas, brain tumors demanding specialized understanding for effective therapeutic interventions. Physiology and Function of Glial Cells in Health and Disease...
Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern...
The application of genetic engineering techniques by redesigning and repurposing biological systems for novel biotechnical applications has paved the way for the field of synthetic biology. This field boosted the evolution and discovery of various novel technologies essential to the conquest of biological problems related to health, disease, the environment, and energy. The field of synthetic biology is growing rapidly, and further research is required. Applications of Synthetic Biology in Health, Energy, and Environment deliberates on principles and the advancement of synthetic biology and their translation in the fields of health, disease, energy, and the environment. Covering topics such as climate change, bioremediation, and smart drugs, this premier reference source is an excellent resource for students and educators of higher education, industrialists, medical professionals, hospital administrators, policymakers, environmental scientists, pharmacists, librarians, researchers, and academicians.
Low temperature plasma in medicine is a new field that rose from the research in the application of cold plasmas in bioengineering. Plasma medicine is an innovative and promising multidisciplinary novel field of research covering plasma physics, life sciences, and clinical medicine to apply physical plasma for therapeutic applications. Emerging Developments and Applications of Low Temperature Plasma explores all areas of experimental, computational, and theoretical study of low temperature and atmospheric plasmas and provides a collection of exciting new research on the fundamental aspects of low temperature and pressure plasmas and their applications. Covering topics such as carbon nanotubes, foodborne pathogens, and plasma formation, this book is an essential resource for research groups, plasma-based industries, plasma aerodynamics industries, metal and cutlery industries, medical institutions, researchers, and academicians.