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There is an ever-increasing emphasis on evidence-based medicine that is distinguished by systematic crafting of the patient-centered research question, detailed literature searches, and careful appraisal of the resulting evidence. The consensus that ultimately emerges must then be applied in specific clinical settings, and it is to this process that translational effectiveness analysis refers. This portable and easy-to-use handbook is intended as a practical teaching guide on translational effectiveness for students and clinicians. Specifically, it will serve as a primer on patient-centered outcomes research methodology in the health sciences and explain how to acquire and understand the fundamental data that determine which reports are valued as the “best available” evidence. It presents an accessible and readily intelligible set of principles which doctors, dentists, nurses, and insurance carriers will be able to use in the process of health care-related decision-making. ​
This book is designed to enable dentists to understand various aspects of dental sleep medicine, and to recognize the signs and symptoms of sleep disorders in their patients. It discusses potential negative impact of a sleep disorder on oral and systemic health, and shows how to collaborate with others in order to implement appropriate patient management. The first part of the book concentrated on the scientific background of sleep medicine in connection to dentistry covering the physiology of sleep, classifications of sleep disorders, their diagnosis as well as medical and dental comorbidities. The second part of the book is dedicated to clinical applications like CPAP therapy, oral appliance therapy, surgical procedures and adjunct therapies. Last, the future of dental sleep medicine is discussed. Each chapter is written by specialized researchers and clinicians in the field making the book a useful guide for dental clinicians all around the world.
All About Bioinformatics: From Beginner to Expert provides readers with an overview of the fundamentals and advances in the _x001F_field of bioinformatics, as well as some future directions. Each chapter is didactically organized and includes introduction, applications, tools, and future directions to cover the topics thoroughly. The book covers both traditional topics such as biological databases, algorithms, genetic variations, static methods, and structural bioinformatics, as well as contemporary advanced topics such as high-throughput technologies, drug informatics, system and network biology, and machine learning. It is a valuable resource for researchers and graduate students who are interested to learn more about bioinformatics to apply in their research work. - Presents a holistic learning experience, beginning with an introduction to bioinformatics to recent advancements in the field - Discusses bioinformatics as a practice rather than in theory focusing on more application-oriented topics as high-throughput technologies, system and network biology, and workflow management systems - Encompasses chapters on statistics and machine learning to assist readers in deciphering trends and patterns in biological data
Global Virology, Volume III: Virology in the 21st Century examines work that has been undertaken, or is planned, in several fields of virology, in an effort to promote current and future work, research, and health. Fields and methods addressed include virology, immunology, space research, astrovirology/astrobiology, plasmids, swarm intelligence, bioinformatics, data-mining, machine learning, neural networks, critical equations, and advances in biohazard biocontainment. Novel and forward-looking methods, techniques, and approaches in research and development are presented by experts in the field.
Maintaining the same accessible and hands-on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real-world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields. Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials. This extensive update of Introductory Biostatistics, Second Edition includes: • A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs • A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes • R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software • Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts • Notes on Computations sections to provide further guidance on the use of software • A related website that hosts the large data sets presented throughout the book Introductory Biostatistics, Second Edition is an excellent textbook for upper-undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.
This edited volume is a definitive text on adaptive clinical trial designs from creation and customization to utilization. As this book covers the full spectrum of topics involved in the adaptive designs arena, it will serve as a valuable reference for researchers working in industry, government and academia. The target audience is anyone involved in the planning and execution of clinical trials, in particular, statisticians, clinicians, pharmacometricians, clinical operation specialists, drug supply managers, and infrastructure providers. In spite of the increased efficiency of adaptive trials in saving costs and time, ultimately getting drugs to patients sooner, their adoption in clinical development is still relatively low. One of the chief reasons is the higher complexity of adaptive design trials as compared to traditional trials. Barriers to the use of clinical trials with adaptive features include the concerns about the integrity of study design and conduct, the risk of regulatory non-acceptance, the need for an advanced infrastructure for complex randomization and clinical supply scenarios, change management for process and behavior modifications, extensive resource requirements for the planning and design of adaptive trials and the potential to relegate key decision makings to outside entities. There have been limited publications that address these practical considerations and recommend best practices and solutions. This book fills this publication gap, providing guidance on practical considerations for adaptive trial design and implementation. The book comprises three parts: Part I focuses on practical considerations from a design perspective, whereas Part II delineates practical considerations related to the implementation of adaptive trials. Putting it all together, Part III presents four illustrative case studies ranging from description and discussion of specific adaptive trial design considerations to the logistic and regulatory issues faced in trial implementation. Bringing together the expertise of leading key opinion leaders from pharmaceutical industry, academia, and regulatory agencies, this book provides a balanced and comprehensive coverage of practical considerations for adaptive trial design and implementation.
Translational Bioinformatics in Healthcare and Medicine offers an overview of main principles of bioinformatics, biological databases, clinical informatics, health informatics, viroinformatics and real-case applications of translational bioinformatics in healthcare. Written by experts from both technology and clinical sides, the content brings together essential knowledge to make the best of recent advancements of the field. The book discusses topics such as next generation sequence analysis, genomics in clinical care, IoT applications, blockchain technology, patient centered interoperability of EHR, health data mining, and translational bioinformatics methods for drug discovery and drug repurposing. In addition, it discusses the role of bioinformatics in cancer research and viroinformatics approaches to counter viral diseases through informatics. This is a valuable resource for bioinformaticians, clinicians, healthcare professionals, graduate students and several members of biomedical field who are interested in learning more about how bioinformatics can impact in their research and practice. - Covers recent advancements in translational bioinformatics and its healthcare applications - Discusses integrative and multidisciplinary approaches to U-healthcare systems development and management - Bridges the gap among various knowledge domains in the field, integrating both technological and clinical knowledge into practical content
This book offers in-depth reviews of different techniques and novel approaches of using blockchain and artificial intelligence in smart healthcare services. The volume brings 14 reviews and research articles written by academicians, researchers and industry professionals to give readers a current perspective of smart healthcare solutions for medical and public health services. The book starts with examples of how blockchain can be applied in healthcare services such as the care of osteoporosis patients and security. Several chapters review AI models for disease detection including breast cancer, colon cancer and anemia. The authors have included model design and parameters for the benefit of professionals who want to implement specific algorithms. Furthermore, the book also includes chapters on IoT frameworks for smart healthcare systems, giving readers a primer on how to utilize the technology in this sector. Additional use cases for machine learning for gesture learning. COVID-19 management, and sentiment analysis.
Essentials of Research Methodology and Biostatistics—A Comprehensive Guide for Health Care Professionals is a precisely written textbook for undergraduate and postgraduate medical, dental, nursing, physiotherapy, clinical psychology and other allied health care profession students. The book is an excellent attempt towards introducing the students and faculty members to the various research methodologies adopted in the field of health sciences to record health-related data. Salient Features Easy to follow: An applied, user-friendly textbook with self-explanatory simple language and presentation for the students. An example-oriented book: Plenty of examples to equip the students to prepare for exams as well as independently conduct their research activities. Illustrative presentation: Diagrammatic and tabular presentation of content to facilitate quick review and recall of important concepts. Systematic and logical organization: Content organized in systematic and logical manner to facilitate better understanding. Qualitative and quantitative research methods, analysis: Adequate coverage of quantitative as well as qualitative research process, methodology and analysis. Authentic content: Content reviewed, authenticated by a panel of renowned faculty members/experts. Unique content: Several unique topics such as sample size calculation, uses of different parametric and nonparametric statistical tests, methods, qualitative research process, and analysis included, with practical examples from Indian scenario, which are rarely found in other research methodology books. Enormous knowledge in a nutshell: In-depth coverage of all aspects of research methodology and biostatistics in a concise manner. Review questions: About 150 end-of-chapter MCQs, a useful resource for the readers to review their preparation for the university exams and also to prepare for qualifying entrance exams for postgraduate and doctoral courses.
In today's data-driven world, understanding and interpreting statistical information is more critical than ever, especially in medicine, where statistical methods are used to design and analyze clinical trials, study the distribution of disease in populations, and develop new treatments. In the era of evidence-based medicine, Exploring Medical Statistics: Biostatistics, Clinical Trials, and Epidemiology addresses the critical need for a grasp of statistical concepts. This book delves into biostatistics, clinical trials, and epidemiology, offering a robust foundation for understanding and interpreting statistical information in medicine. It explores biostatistics, elucidating fundamental elements such as probability, sampling, and hypothesis testing. The section on clinical trials covers the entire spectrum from trial design to ethical considerations, providing an invaluable resource for researchers navigating the complexities of medical research. Epidemiology, a cornerstone of public health, is examined in the book, offering insights into the distribution and determinants of diseases in populations. The application-focused section further extends the utility of medical statistics, encompassing public health, healthcare policy, and drug development.