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Publisher’s note: This is a 2nd edition due to an article retraction
This book will serve as a primer for both laboratory and field scientists who are shaping the emerging field of molecular epidemiology. Molecular epidemiology utilizes the same paradigm as traditional epidemiology but uses biological markers to identify exposure, disease or susceptibility. Schulte and Perera present the epidemiologic methods pertinent to biological markers. The book is also designed to enumerate the considerations necessary for valid field research and provide a resource on the salient and subtle features of biological indicators.
Preceded by Genomics and clinical medicine / edited by Dhavendra Kumar. [First edition]. 2008.
How can a smartwatch help patients with diabetes manage their disease? Why can’t patients find out prices for surgeries and other procedures before they happen? How can researchers speed up the decade-long process of drug development? How will "Precision Medicine" impact patient care outside of cancer? What can doctors, hospitals, and health systems do to ensure they are maximizing high-value care? How can healthcare entrepreneurs find success in this data-driven market? A revolution is transforming the $10 trillion healthcare landscape, promising greater transparency, improved efficiency, and new ways of delivering care. This new landscape presents tremendous opportunity for those who are ready to embrace the data-driven reality. Having the right data and knowing how to use it will be the key to success in the healthcare market in the future. We are already starting to see the impacts in drug development, precision medicine, and how patients with rare diseases are diagnosed and treated. Startups are launched every week to fill an unmet need and address the current problems in the healthcare system. Digital devices and artificial intelligence are helping doctors do their jobs faster and with more accuracy. MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market, which includes interviews with dozens of healthcare leaders, describes the business challenges and opportunities arising for those working in one of the most vibrant sectors of the world’s economy. Doctors, hospital administrators, health information technology directors, and entrepreneurs need to adapt to the changes effecting healthcare today in order to succeed in the new, cost-conscious and value-based environment of the future. The authors map out many of the changes taking place, describe how they are impacting everyone from patients to researchers to insurers, and outline some predictions for the healthcare industry in the years to come.
This book provides a comprehensive and up-to-date review of all aspects of childhood Acute Lymphoblastic Leukemia, from basic biology to supportive care. It offers new insights into the genetic pre-disposition to the condition and discusses how response to early therapy and its basic biology are utilized to develop new prognostic stratification systems and target therapy. Readers will learn about current treatment and outcomes, such as immunotherapy and targeted therapy approaches. Supportive care and management of the condition in resource poor countries are also discussed in detail. This is an indispensable guide for research and laboratory scientists, pediatric hematologists as well as specialist nurses involved in the care of childhood leukemia.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Next-generation sequencing technologies have the capacity to generate large numbers of DNA sequence reads at relatively high speed and low cost. These technologies have revolutionized biomedical research and are increasingly employed in clinical settings, where they can be used to detect inherited disorders, predict disease risk, and personalize therapies. Written and edited by experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine examines next-generation sequencing technologies and their use, particularly in translational research. The contributors discuss the various sequencing platforms, their capabilities, and their applications in both research and clinical practice. The roles of next-generation sequencing in diagnosing autism and intellectual disabilities, monitoring cancers during disease progression, and determining the most appropriate drug treatments for patients are also covered. In addition, the authors consider the practical challenges (e.g., data storage) and ethical implications of using next-generation sequencing technologies. This volume is therefore an essential read for all scientists and physicians interested in these technologies and how they are impacting biomedicine.
Applied Genomics and Public Health examines the interdisciplinary and growing area of how evidence-based genomic knowledge can be applied to public health, population health, healthcare and health policies. The book gathers experts from a variety of disciplines, including life sciences, social sciences, and health care to develop a comprehensive overview of the field. In addition, the book delves into subjects such as pharmacogenomics, genethics, big data, data translation and analysis, economic evaluation, genomic awareness and education, sociology, pricing and reimbursement, policy measures and economic evaluation in genomic medicine. This book is essential reading for researchers and students exploring applications of genomics to population and public health. In addition, it is ideal for those in the biomedical sciences, medical sociologists, healthcare professionals, nurses, regulatory bodies and health economists interested in learning more about this growing field. - Explores the growing application of genomics to population and public health - Features internationally renowned contributors from a variety of related fields - Contains chapters on important topics such as genomic data sharing, genethics and public health genomics, genomics and sociology, and regulatory aspects of genomic medicine and pharmacogenomics
The two-volume set LNBI 11465 and LNBI 11466 constitutes the proceedings of the 7th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2019, held in Granada, Spain, in May 2019. The total of 97 papers presented in the proceedings, was carefully reviewed and selected from 301 submissions. The papers are organized in topical sections as follows: Part I: High-throughput genomics: bioinformatics tools and medical applications; omics data acquisition, processing, and analysis; bioinformatics approaches for analyzing cancer sequencing data; next generation sequencing and sequence analysis; structural bioinformatics and function; telemedicine for smart homes and remote monitoring; clustering and analysis of biological sequences with optimization algorithms; and computational approaches for drug repurposing and personalized medicine. Part II: Bioinformatics for healthcare and diseases; computational genomics/proteomics; computational systems for modelling biological processes; biomedical engineering; biomedical image analysis; and biomedicine and e-health.