Books in Life sciences

Elsevier's Life Science collection helps researchers get comprehensive coverage and up-to-date information on the study of living organisms, their processes, and interrelationships, spanning disciplines like biology, genetics, and biochemistry, and addressing emerging trends such as genomics, biotechnology, and sustainability, essential for advancing knowledge and driving innovation in the field.

Books Journals

1-10 of 9897 results in All results

Vascular Inflammation

1st Edition
December 31, 2099
Johannes Waltenberger
English

Vascular Inflammation: A Novel Understanding of Vascular Diseases and Innovative Strategies for Prevention presents a novel approach to understanding vascular function, vascular dysfunction and vascular diseases. In this title, renowned international experts provide answers with regards to the definition of vascular inflammation, explore a range of relevant aspects of the concept, along with their impact in both understanding as well as treating vascular inflammation and its consequences. Topic include history, mechanisms, genetic basis, disease manifestations and treatment approaches. This cross-disciplinary book is intended for researchers and physicians in the fields of vascular biology, immunology and atherosclerosis. Although there is a large and growing body of evidence about the functional impact of vascular inflammation, the concept as such has never been well defined. Vascular Inflammation is key in understanding any vascular pathology, as well as vascular development and physiological vascular function.

Electrocardiography

1st Edition
December 31, 2099
Anthony Kashou
English

Electrocardiography: Best Cases from Our Practice covers the latest trends in electrocardiology recording software and devices making their way into clinical practice. The book's case studies offer practical guidance for researchers and clinicians on interpreting electrocardiographic data from multiple sources to improve patient outcomes, providing useful reference points for professionals seeking to apply seemingly abstract data points toward individuals’ concrete health goals.The role of cardiac electrical analysis in clinical practice is indispensable. Accordingly, recent advancements in electrocardiological technology have been staggering. Yet, this profusion of disparate recording devices has challenged medical professionals seeking clear-cut strategies for interpreting electrocardiographic data.

Studying Ageing and Disease in Laboratory Mice

1st Edition
December 1, 2099
Ilaria Bellantuono + 1 more
English

Studying Ageing and Disease in Laboratory Mice: A Handbook reviews mouse models commonly used in studies on ageing. The book highlights the advantages and disadvantages of different strategies and discusses their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, examples of models of delayed or accelerated ageing and their modulation by caloric restriction are discussed. With the focus on laboratory mice models, the book provides a toolbox of techniques which can be used to consistently assess their health span. Topics discussed include assessing ageing in rodents, available models, and experimental plans and protocols. This book is valuable resource for researchers, scientists and professionals, but will also be ideal for students and practitioners who wish to broaden their knowledge in the field.

Artificial Intelligence Techniques for Cardiovascular Disease

1st Edition
December 1, 2099
Ankush D Jamthikar + 1 more
English

Artificial Intelligence Techniques for Cardiovascular Disease gives detailed insights into CVD risk assessment using non-invasive carotid imaging under the paradigm of artificial intelligence. The book initially presents global statistics of CVD along with the current standard-of-care screening tools. It provides a deep understanding of carotid atherosclerosis, the anatomy of the carotid artery, how carotid imaging can capture several atherosclerotic plaque characteristics automatically, and the link between these automated carotid artery plaque characteristics with the coronary artery disease. This book further explains the use of carotid atherosclerotic plaque characteristics for short-term and long-term CVD risk assessment using machine learning and deep learning algorithms. A novel approach to CVD risk prediction by combining conventional cardiovascular risk predictors with carotid ultrasound image-based phenotypes is also discussed and compared against the conventional CVD risk prediction algorithms. Lastly, this book provides applications of CVD risk assessment in several comorbidities such as rheumatoid arthritis, chronic kidney disease, diabetes, coronary artery disease, HIV, and COVID-19. Artificial Intelligence Techniques for Cardiovascular Disease is for those interested in using artificial intelligence techniques for CVD and stroke risk assessment.

Algorithms in Computational Biology

1st Edition
December 1, 2099
David C. Molik
English

Algorithms in Computational Biology takes a deep dive into the tools used and common problems in bioinformatics (e.g.: sequence alignment, ordination) and explores the underlying algorithms that make them run. The algorithms used in sequence alignment come from an older problem in Computer Science called Fuzzy String Matching, or sometimes Inexact String Matching, from which an understanding of the solutions to these older problems imparts a stronger understanding of the Sequence Alignment problem. By briefly looking at the history of the problem and solutions, and then taking a deeper look at the mechanics of the algorithm, readers will improve their understanding of their science and be more able to accurately and efficiently implement solutions in Computational Biology. Each chapter of the book provides its own look at a problem-algorithm pairing. Each chapter is comprised of a brief history, which describes the problem, then restates the problem more succinctly in algorithmic and mathematical terms, and then presents known solutions to those algorithms. The book begins with a "state of computational biology" Introduction, and ends with a concluding chapter wherein the next problems of computational biology are described and explored. This book is intended to be an independent resource for someone wanting to learn more about computational biology, formatted in an interesting and accessible way. Algorithms in Computational Biology provides a bridge for Computational Scientists, talking about something they know: the algorithm, and Biologists, talking about something they know: the biology. By making the other half just accessible enough, and walking that line, both can gain a deeper understanding and appreciation for the other.

Accelerated Dynamic Magnetic Resonance Imaging

1st Edition
Volume TBD
December 1, 2099
Jennifer Steeden + 1 more
English

Magnetic Resonance Imaging (MRI) scans play a vital role in diagnosis and monitoring of diseases across the body. However, MRI is a relatively slow imaging technology, resulting in long scan times. This is particularly challenging when imaging dynamic processes. Accelerated Dynamic Magnetic Resonance Imaging: Methods and Applications explains the technologies which can speed up MRI imaging and shows how they have been applied to a broad range of application areas, presenting the challenges and giving practical advice on implementation. With this book the reader will be able to: Modify the MRI sequences to speed up acquisition of data (non-Cartesian trajectories and data under sampling); Use the techniques (parallel imaging, compressed sensing and machine learning) which are commonly used to reconstruct under sampled MRI data; Implement fast MRI imaging techniques for their application areas. Accelerated Dynamic Magnetic Resonance Imaging: Methods and Applications is an ideal resource for the technologist, clinical researcher and clinician who want to understand rapid MRI methods and gain practical advice on their implementation.

Machine and Deep Learning for Automated Diagnosis of Critical diseases

1st Edition
December 1, 2099
Kalpana Chauhan + 1 more
English

When diagnosing critical disease a timely and accurate detection of the problems or symptoms experienced by the patient is critical. Machine and deep learning methods provide the technology to create quicker and more accurate diagnoses by automating the detection process.This book presents advanced machine and deep learning methods for automating the diagnosis of critical disease. It provides the methods and algorithms for analyzing complex images to diagnose disease. The types of diseases it covers are coronary artery, cancer, tumours, lung and kidney.This book is a comprehensive resource for engineers or computer scientists looking to apply machine and deep learning methods to image analysis for the purpose of diagnosing disease.

An Introduction to Artificial Intelligence for Clinicians

1st Edition
December 1, 2099
Pearse A Keane + 4 more
English

An Introduction to Artificial Intelligence for Clinicians: A Practical Guide to Clinical AI for Healthcare Professionals addresses the rapidly expanding field of clinical artificial intelligence and the potential it holds for healthcare professionals and their patients. It enables readers to create their own deep learning project and build a model using code-free deep learning. It also provides them with a comprehensive overview of the statistics used in clinical AI and methods to critically appraise clinical AI papers. By equipping clinicians with education and skills they can use in the present world of clinical AI, they are better positioned for the future arrival of artificial intelligence into day-to-day patient care. To ensure the broad relevance of this book, the editors also draw on a yet unpublished qualitative evidence synthesis of stakeholder experiences of AI implementation across all healthcare contexts worldwide, which empowers readers to see how clinical AI could benefit patients in their own context and to inspire others to affect change. It is a valuable resource for clinicians, students, researchers, healthcare professionals and members of medical and biomedical fields who are interested to learn more about artificial intelligence applied to clinical setting and healthcare.

Contemporary View of Functional Urology

1st Edition
December 1, 2099
Michael Samarinas D
Michael Samarinas D
English

Contemporary View on Functional Urology: Novel Theories and Treatments on Lower Urinary Tract Dysfunction provides novel theories and treatments in functional urology for lower urinary tract dysfunction. Content covers various types of lower urinary tract dysfunction, independent of pathophysiology, age, or gender. It includes clinical examination, specific noninvasive instruments like questionaries, ultrasound, or uroflow, and invasive techniques like urodynamic and video-urodynamic studies. Content is targeted to include high-level, evidenced, scientific information that guides the reader, resulting is a full understanding of functional urology with novel pathophysiological theories, new treatment approaches, and clinical and surgical developments.This is the perfect reference to equip practicing urologists with an understanding of the importance of functional urology approaches in everyday clinical practice. It will also be useful for lower urinary tract dysfunction translational researchers who want to be more familiar with novel pathophysiological theories in functional urology.

Multimodal Neuroimaging

1st Edition
December 1, 2099
Peter J. Molfese
English

Understanding the brain began with black-box psychological experiments seeking to understand basic inputs and outputs. As technology has advanced, neuroimaging techniques have developed to see inside the system with various tradeoffs. While each technology presents technical challenges, it is now recognized that the combination of multiple neuroimaging techniques yields information beyond the sum of the parts. Multimodal Neuroimaging: Theory and Methods gives the theoretical background to, and practical applications of, neuroimaging technologies. It uses multiple tools including EEG, fMRI, MEG, TMS, neuromodulation and shows how to combine data from multiple sources into a more coherent picture for understanding the brain. Multimodal Neuroimaging: Theory and Methods enables graduate students and researchers to identify methods, theory and applications relevant to their area of interest and gain a fundamental understanding of the steps needed to implement multimodal neuroimaging in their work