Epidemiology and Medical statistics

For many centuries, people have tried to learn about the state of their health.

This textbook provides basic quantitative models allowing researchers and decision makers to a) assess viability of threatened populations and evaluate the success of species reintroductions, b) estimate invasion abilities of alien species, c) evaluate the persistence of metapopulations subjected to habitat destruction and fragmentation, d) analyze policies and strategies for the sustainable harvesting of biological resources, and e) assess the course of human and nonhuman diseases and the possible containment measures.

Dieses Buch gibt eine Einführung in die Analyse multivariater Daten.

An authoritative, evidence-based overview of the health needs of people with intellectual disabilities and how to manage these needs appropriately.

This volume comprises the investigation of factors that may predict the response to treatment, outcome, and survival by exploring: design considerations in molecular epidemiology, including:case-onlyfamily-basedapproaches for evaluation of genetic susceptibility to exposure and addiction pharmacogeneticsincorporation of biomarkers in clinical tria

"e;The OHE Compendium of Health Statistics"e; is the one-stop statistical source specially designed for easy use by anyone interested in the UK health care sector and the NHS.

Outlines the development and application of a variety of patient-reported outcome measures in a wide range of neurological conditions.

This new edition of Medical Statistics Made Easy 2nd edition enables readers to understand the key statistical techniques used throughout the medical literature.

Orthopoxviruses Pathogenic for Humans covers those viruses capable of causing disease in man, including monkeypox, smallpox, cowpox, and vaccinia.

The book provides a comprehensive examination of pancreatic cancer, integrating global insights with an African-focused perspective.

A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible.

Healthcare and medical science are inherently dependent on technological advances and innovations for improved care.

This second edition of Epidemiologic Methods offers a rigorous introduction to the concepts and tools of epidemiologic research.

This book is dedicated to Dr.

This volume of the series Advances in Risk Analysis consists of papers presented at the 1988 Annual Meeting of the Society for Risk Analysis, which was held October 30 through November 2 at the Mayflower Hotel in Washington, DC.

An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.

This book covers recent developments in epidemic process models and related data on temporally varying networks.

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19.

Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data shows how the Bayesian approach to inference is applicable to partially identified models (PIMs) and examines the performance of Bayesian procedures in partially identified contexts.

This handbook provides thorough, in-depth, and well-focused developments of artificial intelligence (AI), machine learning (ML), deep learning (DL), natural language processing (NLP), cryptography, and blockchain approaches, along with their applications focused on healthcare systems.

An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer.

Diagnosis through images, robot surgeons, digital twins, and the metaverse are some of the applications in which artificial intelligence (AI) is involved.

"e;Provides current models, tools, and examples for the formulation and evaluation of scientific hypotheses in causal terms.

Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting.

Preventive medical interventions and non-medicalised public health programmes that promise health benefits in the future, from actions taken now, carry a strong ethical requirement of 'first, do no harm' or primum non nocere.

Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment.

Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment.

A thorough treatment of the statistical methods used to analyze doubly truncated data In The Statistical Analysis of Doubly Truncated Data, an expert team of statisticians delivers an up-to-date review of existing methods used to deal with randomly truncated data, with a focus on the challenging problem of random double truncation.

Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective.

This book describes the integration of high-throughput bioinformatics data from multiple platforms to inform our understanding of the functional consequences of genomic alterations.

As the health delivery landscape in the United States evolves in a post-COVID-19 era, both incumbents and new entrants are reimagining models of care.

Patients with unmet needs will continue to increase as no viable nor adequate treatment exists.

Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times.

The definitive textbook on the subject, offering a core curriculum that addresses the epidemiology of major reproductive and perinatal outcomes.

This book is intended to show the great achievements and valuable experience of Chinese public health practices and epidemiological theories and methods.

This book presents advanced research on smart health technologies, focusing on the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques.

Disease is an ever-present threat faced by all human societies.

This book introduces basic concepts, principle, and methods of medical statistics systematically and practically, especially in the statistical design of the experiment in terms of the specific problems, adequate use of statistical methods based on actual data and the reasonable explanation for statistical results.

This book addresses the origins, determinants and magnitude of the global problem of sedentary behaviour, along with concise yet in-depth solutions for tackling it.

This book addresses the COVID-19 pandemic from a quantitative perspective based on mathematical models and methods largely used in nonlinear physics.

Leading scholars and practitioners come together in this contributed volume to present the most current evidence on cutting edge health issues for South Asian Americans, the fastest growing Asian American population.

R for Health Technology Assessment discusses the use of proper statistical software, specifically R, to perform the whole pipeline of analytic modelling in health technology assessment (HTA).

Brings together the insights of genetic and molecular science to protect and improve public health.

Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background.

COVID-19 Management in the Brain and Body describes the management of patients with the novel coronavirus in their varied symptoms.

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients' privacy and data security including data breaches in healthcare organizations, unauthorized access to patients' information, and medical identity theft.