Translational Informatics

Integrative and translational methodologies and frameworks have transformed modern biomedical research and the delivery of clinical care. This shift has been manifested in a number of ways, including the rapid growth and increasing availability of high-throughput bio-molecular instrumentation and analysis platforms, innovative clinical research programs intended to accelerate knowledge translation, and initial efforts to deliver personalized healthcare informed by the genomic profiles of patients. A common theme of reports and publications concerned with such transformative changes in the biomedical and healthcare domains is concerned with the challenges and opportunities related to the collection, management, integration, analysis, and dissemination of large-scale, heterogeneous biomedical data sets. In particular, the absence of well-established and adopted theoretical and practical frameworks intended to address such needs is a major impediment to the realization of translational and knowledge-driven healthcare, in which the best possible scientific evidence is used to inform the care of every patient. In this vacuum, the development of integrative clinical or translational research paradigms is significantly limited by the propagation of both data and expertise silos. This book details for the first time the current state of this extremely potent area of healthcare innovation and policy and defines the interaction between clinical/translational science and biomedical informatics.​

This book introduces the translational informatics applied to most aspects of virus infection, including tracking of virus origin, detection and prevention of infection, drug discovery, and vaccine design as well as smart city-level monitoring and controlling of the virus epidemic by government. It covers the informatics for data mining and modelling at molecular, tissue/organ, individual, and population levels. The informatics for immunological mechanisms and the personalized prediction and treatment of infected patients are also summarized. The perspectives on the application of artificial intelligence to the prevention of virus outbreaks are also given. This book will be helpful to readers who are interested in prevention of virus infection, biomedical informatics, and artificial intelligence in medicine and healthcare.

This book is about the transformation of the biomedical information to smart healthcare, the chapters are designed to discuss the health associated factors such as genetics, lifestyle, nutrition and environmental factors. The interactions of these factors and the informatics for the analyses of their effects on health are also covered. The era of aging is approaching and the P4 (predictive, preventive, personalized and participatory) medicine paradigm is becoming practical and reality. According to the Kondratiev's long wave theory, IT (information technology) and health will be the next technological revolution for the new economic cycle. This book is written for biomedical informatics scientists, clinicians, health practitioners and researchers, etc.

Integrative and translational methodologies and frameworks have transformed modern biomedical research and the delivery of clinical care. This shift has been manifested in a number of ways, including the rapid growth and increasing availability of high-throughput bio-molecular instrumentation and analysis platforms, innovative clinical research programs intended to accelerate knowledge translation, and initial efforts to deliver personalized healthcare informed by the genomic profiles of patients. A common theme of reports and publications concerned with such transformative changes in the biomedical and healthcare domains is concerned with the challenges and opportunities related to the collection, management, integration, analysis, and dissemination of large-scale, heterogeneous biomedical data sets. In particular, the absence of well-established and adopted theoretical and practical frameworks intended to address such needs is a major impediment to the realization of translational and knowledge-driven healthcare, in which the best possible scientific evidence is used to inform the care of every patient. In this vacuum, the development of integrative clinical or translational research paradigms is significantly limited by the propagation of both data and expertise silos. This book details for the first time the current state of this extremely potent area of healthcare innovation and policy and defines the interaction between clinical/translational science and biomedical informatics.​

This issue of the Clinics in Laboratory Medicine, edited by Dr. Anil Parwani, is a special issue is devoted to topics in Pathology Informatics. Topics include but are not limited to: Basics of Information Systems (Hardware, Software); Networks, Interfaces and Communications; Databases; Laboratory Information Systems; Enhancing and Customizing Laboratory Information Systems; Laboratory Management and Operations; Specialized Laboratory Information Systems; Bar Coding and Tracking; Molecular Pathology Informatics; Pathology Informatics and Project Management; Digital Imaging; Telepathology; Healthcare Information Systems; Data Security and Reliability; Role of Pathology Informatics in IT Leadership; Selection and Implementation of New Information Systems; Biomedical Informatics and Research Informatics; Training in Pathology Informatics; and more.

Beginning with a survey of fundamental concepts associated with data integration, knowledge representation, and hypothesis generation from heterogeneous data sets, Methods in Biomedical Informatics provides a practical survey of methodologies used in biological, clinical, and public health contexts. These concepts provide the foundation for more advanced topics like information retrieval, natural language processing, Bayesian modeling, and learning classifier systems. The survey of topics then concludes with an exposition of essential methods associated with engineering, personalized medicine, and linking of genomic and clinical data. Within an overall context of the scientific method, Methods in Biomedical Informatics provides a practical coverage of topics that is specifically designed for: (1) domain experts seeking an understanding of biomedical informatics approaches for addressing specific methodological needs; or (2) biomedical informaticians seeking an approachable overview of methodologies that can be used in scenarios germane to biomedical research. Contributors represent leading biomedical informatics experts: individuals who have demonstrated effective use of biomedical informatics methodologies in the real-world, high-quality biomedical applications Material is presented as a balance between foundational coverage of core topics in biomedical informatics with practical "in-the-trenches" scenarios. Contains appendices that function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4) Web Services.

Nursing Informatics and the Foundation of Knowledge, Fifth Edition is a foundational text for teaching nursing students the core concepts of knowledge management while providing an understanding of the current technological tools and resources available.

The book provides readers the informatics and data-driven models for the discovery of personalized excise prescriptions applied to different cases. Overdiagnosis or over-treatment often happened since the complex interaction among the lifestyle, genetic, and environmental factors. Sports and exercise are reported efficient to prevent or reduce the risk of diseases, but the interactions between sports/exercise and disease are personalized and complex. Translational informatics is a powerful paradigm and it promotes the transfer of big data, knowledge and models to the precision application of sports to prevent diseases. Sports and exercise may have different effects on diverse diseases including cancers, neurodegenerative disease, and cardiovascular diseases, etc. This book covers many modern informatics models such as ontologies, knowledge graphs, blockchain, participatory medicine, semantic artificial intelligence, big data modeling, and so on. It also describes the challenges for the sports and exercise medical data sharing and standardization, the privacy protection of data as well as the integration of data from genomic level to physiological phenotype level. This book will be helpful to the readers who are interesting in sports and exercise medicine, healthcare, big data modeling, artificial intelligence in medicine and healthcare.