Artificial Intelligence (AI) innovations in digital health offer unprecedented opportunities to facilitate human health and provide tools and techniques that reduce overall costs.
"e;Biomedical Imaging: Principles and Advancements"e; offers a captivating exploration of the intricate landscapes within the human body, revealing the transformative power of biomedical imaging.
Die Simulation des menschlichen Herzens, die Vorhersage des morgigen Wetters, die Optimierung der Aerodynamik eines Segelboots, die Suche nach der idealen Garzeit für einen Hamburger: Bei der Lösung dieser Probleme können Kardiologen, Meteorologen, Sportler und Ingenieure auf mathematische Hilfe zählen.
Die Simulation des menschlichen Herzens, die Vorhersage des morgigen Wetters, die Optimierung der Aerodynamik eines Segelboots, die Suche nach der idealen Garzeit für einen Hamburger: Bei der Lösung dieser Probleme können Kardiologen, Meteorologen, Sportler und Ingenieure auf mathematische Hilfe zählen.
Drawing from the authors' own work and from the most recent developments in the field, Missing Data in Longitudinal Studies: Strategies for Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal studies.
Nonpharmacological treatments include a wide variety of treatments such as surgery, technical procedures, implantable and non-implantable devices, rehabilitation, psychotherapy, and behavioral interventions.
This textbook provides a comprehensive introduction to the factors that impact physical, mental, and social well-being, offering a broad definition of health and healthcare that moves beyond the biomedical model.
This reference book comprehensively delves into the systematics, taxonomy, morphology, ecology, and behaviour of the Lepidostomatidae (Trichoptera) in India.
This book provides an introduction to ethics, research design as the most important part of the qualitative research process, the importance of theoretical frameworks and the relationship between the researcher and the researched in the qualitative research process.
Distinctively, this book brings together an end-to-end understanding of heatwaves, that is, a consideration of their causes, consequences for human and natural systems and societal responses to them in the form of adaptation and mitigation actions.
Distinctively, this book brings together an end-to-end understanding of heatwaves, that is, a consideration of their causes, consequences for human and natural systems and societal responses to them in the form of adaptation and mitigation actions.
Hospitals in the US and Canada are ill-prepared for the threat of emerging infectious diseases, especially in the area of protecting healthcare workers, nurses, doctors, and first responders from transmissions.
This concise guide equips readers with the essential skills required to analyze and critically appraise health research evidence, an integral element to evidence-based practice and professional development.
Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent techniques, models, and computational tools for interval-censored time-to-event data.
Practical Statistical Methods: A SAS Programming Approach presents a broad spectrum of statistical methods useful for researchers without an extensive statistical background.
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data.
Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology.
This textbook provides a comprehensive introduction to the factors that impact physical, mental, and social well-being, offering a broad definition of health and healthcare that moves beyond the biomedical model.
While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners.
Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data.
An in-depth overview on the demo-graphic changes occurring world-wide and the repercussions this is having on the pattern of vector-borne disease is pre-sented in this book.
El espejo de la pandemia ha permitido rescatar diferentes formas de analisis de la realidad social en salud, de manera que, para el caso de esta obra, se conjugue el juicioso analisis epidemiologico de la Encuesta Nacional de Salud Mental de 2015 con la aproximacion desde las ciencias sociales, la lectura de determinantes contextuales y, en particular, la descripcion que permite el analisis espacial.
Featuring contributions from leading scholars of health privacy law, this important volume offers insightful reflection on issues such as confidentiality, privacy, and data protection, as well as analysis in how a range of jurisdictions-including the US, the UK, Europe, South Africa, and Australia-navigate a rapidly developing biomedical environment.
As evidenced by the anthrax attacks in 2001, the SARS outbreak in 2003, and the H1N1 influenza pandemic in 2009, a pathogen does not recognize geographic or national boundaries, often leading to devastating consequences.
As doctors and biologists have learned, to their dismay, infectious disease is a moving target: new diseases emerge every year, old diseases evolve into new forms, and ecological and socioeconomic upheavals change the transmission pathways by which disease spread.
Structural Health Monitoring and Integrity Management is a collection of the papers presented at the 2nd International Conference of Structural Health Monitoring and Integrity Management (ICSHMIM2014, Nanjing, China, 24-26 September 2014), and addresses the most recent developments in the field of Structural Health Monitoring (SHM) and integrity ma
Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged.