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Big data analytics and machine intelligence in biomedical and health informatics : Concepts, methodologies, tools and applications
Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. Covers the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).
AI in clinical practice : A guide to artificial intelligence and digital medicine
Explains how artificial intelligence is applied to medicine, illustrating not only its enormous potential but also ancillary issues and the limits and risks inherent in its use on a large scale. The book focuses on the intersection between medicine and AI and its implications on the impact of human health care delivery. Topics discussed include wearable devices, health data, Internet of Things, virtual reality, robotic assistance system, and digital intelligence in the health sector. Additionally, sections discuss diagnostics and decision-making systems and machine/deep learning in clinical setting.
CADD and informatics in drug discovery
Updates knowledge on recent advances in computational and bioinformatics tools/techniques and their practical applications in modern drug design and discovery programme. Also it encompasses fundamental principles, advanced methodologies and applications of various CADD approaches including several cutting-edge areas / presenting recent developments covering ongoing trends in the field of computer-aided drug discovery. Having contributions by a global team of experts, the book is expected to be an ideal resource for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, phytochemists, biochemists, biologists, RandD personnel, researchers, students, teachers and those working in the field of drug discovery. It will fill the knowledge gaps that exist in the current CADD approaches and methodologies/ protocols being widely used in both academic and research practices. Further, a special focus on current status of various computational drug design approaches (SBDD, LBDD, De-novo drug design, Pharmacophore-based search), bioinformatics tools and databases, computational screening and modeling of phytochemicals/natural products, artificial intelligence and machine learning, and network pharmacology and system biology would certainly guide researchers, students or readers to conduct their research in the emerging area(s) of interest. It is also expected to be highly beneficial to different stakeholders working in the pharmaceutical and biotechnology industries (RandD), the academic as well as research sectors. .
Biomedical applications and toxicity of nanomaterials
Covers the recent trends on the biological applications of nanomaterials, methods for their preparation, and techniques for their characterization. Further, the book examines the fundamentals of nanotoxicity, methods to assess the toxicity of engineered nanomaterials, approaches to reduce toxicity during synthesis. It also provides an overview of the state of the art in the application of Artificial intelligence-based methodologies for evaluation of toxicity of drugs and nanoparticles. The book further discusses nanocarrier design, routes of various nanoparticle administration, nano based drug delivery systems, and the toxicity challenges associated with each drug delivery method. It presents the latest advances in the interaction of nanoparticles with the cellular environment and assess nanotoxicity of these engineered nanoparticles. The book also explores the comparative and mechanistic genotoxicity assessment of the nanomaterials. This book is useful source of information for industrial practitioners, policy makers, and other professionals in the fields of toxicology, medicine, pharmacology, food, and drugs.
Bioinformatics tools for pharmaceutical drug product development
Presents the latest information on bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies. And include bioinformatics tools for the pharmaceutical sector and the healthcare sector. Bioinformatics brings a new era in research to accelerate drug target and vaccine design development, improving validation approaches as well as facilitating and identifying side effects and predicting drug resistance. As such, this will aid in more successful drug candidates from discovery to clinical trials to the market, and most importantly make it a more cost-effective process overall.
Artificial intelligence in drug design
Looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future.
Artificial intelligence based cancer nanomedicine : Diagnostics, therapeutics and bioethics
Nanomedicine is evolving with novel drug formulations devised for multifunctional approaches towards diagnostics ad therapeutics. Nanomedicine-based drug therapy is normally explored at a fixed dose. The drug action is time-dependent, dose-dependent and patient-specific. To overcome challenges of nanomedicine testing, artificial intelligence (AI) serves as a helping tool for optimizing the drug and dose parameters. Real time conversions between these two features enables upgradation of patient data acquisition and improved design of nanomaterials. In this scenario, AI-based pattern analysis and algorithms models can greatly improve accuracy of diagnostics and therapeutics.
An introduction to generative drug discovery
Describes the state‑of‑the‑art methods and applications for de novo design of drug candidates using generative chemistry models as well as the ethical aspects of this technology. It will provide a foundation for those new to the field as well as those that may already have some experience of its utility. With contributions from scientists in both academia and industry ‘Introduction to Generative Drug Discovery’ may represent one of the earliest if not the first book to focus on this topic.
AI in disease detection : Advancements and applications
Discusses the integration of artificial intelligence to revolutionize disease detection approaches, with case studies of AI in disease detection as well as insight into the opportunities and challenges of AI in healthcare as a whole. The book explores a wide range of individual AI components such as computer vision, natural language processing, and machine learning as well as the development and implementation of AI systems for efficient practices in data collection, model training, and clinical validation.
AI in clinical medicine : A practical guide for healthcare professionals
A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future.
About Life : Concepts in Modern Biology
This book uses modern biological knowledge to tackle the question: "What distinguishes living organisms from the non-living world?" In the first few chapters, the authors draw on recent advances in cell and molecular biology to develop an account of the "living state" that applies to all organisms, but only to organisms. Subsequent chapters use this account to explore questions about evolution, the origin of life and the possibility of extraterrestrial life. Towards the end of the book the authors consider human evolution, intelligence and the extent to which our species can be regarded as biologically unique. About Life is written as far as possible in non-technical language; all scientific terms are explained straightforwardly when they are introduced. It is aimed at the general, non-specialist reader, but the novel approach that it takes to general issues in biology will also interest students of the life sciences.
Linked Democracy : Foundations, Tools, and Applications
This book shows the factors linking information flow, social intelligence, rights management and modelling with epistemic democracy, offering licensed linked data along with information about the rights involved. This model of democracy for the web of data brings new challenges for the social organisation of knowledge, collective innovation, and the coordination of actions. Licensed linked data, licensed linguistic linked data, right expression languages, semantic web regulatory models, electronic institutions, artificial socio-cognitive systems are examples of regulatory and institutional design (regulations by design). The web has been massively populated with both data and services, and semantically structured data, the linked data cloud, facilitates and fosters human-machine interaction. Linked data aims to create ecosystems to make it possible to browse, discover, exploit and reuse data sets for applications. Rights Expression Languages semi-automatically regulate the use and reuse of content.
Artificial intelligence and legal analytics : new tools for law practice in the digital age
The field of artificial intelligence (AI) and the law is on the cusp of a revolution. This book - designed to explain computational processes to non-programmers - describes how text analytic programs will change the practice of law, specifically by connecting computational models of legal reasoning directly with legal text.
Artificial Intelligence and International Economic Law : Disruption, Regulation, and Reconfiguration
This book was finalized while countries around the world were still confronting a global public health crisis caused by the COVID-19 pandemic. Many came to rely on digital services as an infrastructure for social interaction and professional endeavors, including academic and educational work. The pandemic seems to have precipitated a further shift towards digital technologies and artificial intelligence. It is our hope that this book will contribute to an informed discussion about the relevance of and implications for international economic law beyond the pandemic"
AI and law : How automation is changing the law
Provides insights into how AI is changing legal practice, government processes, and individuals’ access to those processes, encouraging each of us to consider how technological advances are changing the legal system. Particularly, and distinct from current debates on how to regulate AI, this books focuses on how the progressive merger between computational methods and legal rules changes the very structure and application of the law itself.
Leveraging Data Science for Global Health
Explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources.
Blockchain, artificial intelligence, and the internet of things : Possibilities and opportunities
Provides basic concepts and deep knowledge about various security mechanisms that can be implemented in IoT through Blockchain technology. This book aids readers in gaining insight and knowledge about providing security and solutions to different challenges in IoT using Blockchain technology. This book primarily focuses on challenges to addressing the integration of the IoT with Blockchain with respect to potential benefits for IoT. This book gives descriptive analysis of Blockchain integrated with IoT applications and platforms for the development of IoT solutions along with possible topologies to that integration. Several application examples are included in a variety of industries / Provides the latest on secure IIoT communication using Blockchain technology for Industry 4.0 / Includes updates on using Blockchain technology in secure vehicular communication (VANET), healthcare, retail, and gaming / Provides the latest on secure IIoT communication using Blockchain technology for Industry 4.0
Artificial intelligence in the financial services industry
Today, the financial services sector is facing a period of rapid disruption and innovation, and artificial intelligence (AI) is at the heart of these changes. Artificial intelligence can be used to gather enormous amounts of data, detect abnormalities, and solve complex problems. Financial institutions are already experimenting extensively with AI strategies to enhance and streamline financial institutions, BSA and AML compliance, CRA requirements, fraud detection, and real estate valuations, all while reducing cost levels. This book looks at how artificial intelligence is affecting the financial services industry.
Mathematical Methods in Computer Science : Essays in Memory of Thomas Beth
This Festschrift volume contains the proceedings of the conference Mathematical Methods in Computer Science, MMICS 2008, which was held during December 17-19, 2008, in Karlsruhe, Germany, in memory of Thomas Beth.The themes of the conference reflected the many interests of Thomas Beth. Although, these interests might seem diverse, mathematical methods and especially algebra as a language constituted the common denominator of all of his scientific achievements.
Markov Models for Pattern Recognition : From Theory to Applications
Describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems.
