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The world of pharmaceutical research is moving at lightning speed, and the age-old approach to drug discovery faces many challenges. It's a fascinating time to be on the cutting edge of medical innovation, but it's certainly not without its obstacles. The process of developing new drugs is often time-consuming, expensive, and fraught with uncertainty. Researchers are constantly seeking ways to streamline this process, reduce costs, and increase the success rate of bringing new drugs to market. One promising solution lies in the convergence of pharmacy science and engineering, particularly in computational drug discovery. Converging Pharmacy Science and Engineering in Computational Drug Disco...
Bioactive lipid metabolism and signaling are now widely accepted as major players in cancer biology. This volume helps to fill the urgent need to explore and investigate the innovations, current shortcomings, and future challenges of cancer therapy through the bioactive lipids by presenting new research on the use of bioactive lipids as effective weapons against cancer. The volume introduces the subject and then goes on to cover the chemistry, formulation, and mechanism of bioactive lipids in cancer. The volume takes a close look at lipoxins, ceramides, resolvins, and sphingosine-1-phosphate and their roles in cancer treatment. It also addresses the formulations based on bioactive lipids for...
Numerous phenomenal advances have been made towards understanding the role of neurotransmitters in the pathophysiology of neurological disorders, and these have resulted in a large number of novel molecules with the potential to revolutionize the treatment and prevention of such disorders. This book provides a comprehensive and detailed explanation of brain neurotransmitters and their receptors and associated channels. It includes a basic introduction, and also discusses the functions and recent advances and their pharmacology, highlighting the role of various computer aided drug design (CADD) strategies for the development of therapeutic ligands to modulate these receptors/ion channels. Written in an easy-to-read style, it is intended for neuroscience and pharmaceutical students and researchers working in the area of brain neurotransmitters.
Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of ...
In the realm of healthcare, the persistent challenges of data breaches, centralized systems, and fraudulent claims have posed significant hurdles in ensuring the integrity and security of patient information. The traditional approaches to managing Electronic Health Records (EHR) often fall short, leaving room for exploitation and compromising the confidentiality of sensitive medical data. Enter the transformative solution presented in Blockchain and IoT Approaches for Secure Electronic Health Records (EHR). This groundbreaking book navigates the intricate landscape of healthcare technology, addressing the vulnerabilities in the current systems. By leveraging the power of Blockchain technology, it pioneers a secure peer-to-peer communication system that not only ensures the tamper-proof nature of health records but also revolutionizes the entire healthcare industry. The book is a comprehensive exploration of Blockchain's relevance in healthcare, covering the architecture, scope, and applications that promise to redefine how patient data is managed and protected.
Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions. This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making.
In todays digital age, the healthcare industry is undergoing a paradigm shift towards embracing innovative technologies to enhance patient care, improve efficiency, and ensure data security. With the increasing adoption of electronic health records, telemedicine, and AI-driven diagnostics, robust cybersecurity measures and advanced data management strategies have become paramount. Protecting sensitive patient information from cyber threats is critical and maintaining effective data management practices is essential for ensuring the integrity, accuracy, and availability of vast amounts of healthcare data. Cybersecurity and Data Management Innovations for Revolutionizing Healthcare delves in...
Artificial Intelligence (AI) technology has led to the creation of many opportunities in the field of healthcare. Like other industries, stakeholders in the healthcare sector stand to benefit tremendously from its adoption. The multifaceted benefits associated with AI are something that makes the adoption of technology constructive for the sector. That said, it is equally important to take care of the ethical, security, and safety challenges related to AI applications. AI Healthcare Applications and Security, Ethical, and Legal Considerations discusses in detail the various facets of AI integration in the healthcare sector. This book offers comprehensive information on how to integrate AI into the healthcare sector safely and ethically. Covering topics such as cybersecurity, machine learning models, and public policy, this book is an excellent resource for healthcare professionals and administrators, researchers, ethicists, legal scholars, healthcare policy makers and regulators, medical informatics and IT professionals, educators, bioethics professionals, academicians, and more.
In the field of healthcare technology, the Internet of Medical Things (IoMT) stands at the forefront of progress, revolutionizing patient care through advanced monitoring and treatment modalities. However, this digital transformation brings forth a new challenge the vulnerability of sensitive medical data to cyber threats. Lightweight Digital Trust Architectures in the Internet of Medical Things (IoMT) examines ways to fortify IoMT against potential breaches through the exploration of these trust architectures. Delving deep into data privacy technologies, the book examines the implications of regulatory frameworks such as GDPR, HIPAA, and cybersecurity law. It assesses traditional security...