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Medical bioinformatics

See below for a selection of the latest books from Medical bioinformatics category. Presented with a red border are the Medical bioinformatics books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Medical bioinformatics books and those from many more genres to read that will keep you inspired and entertained. And it's all free!

Data Science for Healthcare

Data Science for Healthcare

Author: Sergio Consoli Format: Hardback Release Date: 07/03/2019

This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.

The Flu Is Coming

The Flu Is Coming

Author: J L Greger Format: Paperback / softback Release Date: 04/12/2018

Design and Implementation of Healthcare Biometric Systems

Design and Implementation of Healthcare Biometric Systems

Author: Dakshina Ranjan Kisku Format: Hardback Release Date: 30/11/2018

Healthcare sectors often deal with a large amount of data related to patients' care and hospital workforce management. Mistakes occur, and the impending results are disastrous for individuals' personal identity information. However, an innovative and reliable way to safeguard the identity of individuals and provide protection of medical records from criminals is already in effect. Design and Implementation of Healthcare Biometric Systems provides innovative insights into medical identity theft and the benefits behind biometrics technologies that could be offered to protect medical records from hackers and malicious users. The content within this publication represents the work of ASD screening systems, healthcare management, and patient rehabilitation. It is designed for educators, researchers, faculty members, industry practitioners, graduate students, and professionals working with healthcare services and covers topics centered on understanding the practical essence of next-generation healthcare biometrics systems and future research directions.

Beginners Guide To Bioinformatics For High Throughput Sequencing

Beginners Guide To Bioinformatics For High Throughput Sequencing

Author: Tin Wee (Nus, S'pore) Tan, Eric Cheng-yu (Nus, S'pore) Lee Format: Paperback / softback Release Date: 29/11/2018

Biologists find computing bewildering; yet they are expected to be able to process the voluminous data available from the machines they buy and the datasets that has accumulated in genomic databanks worldwide. It is now increasingly difficult for them to avoid dealing with large volumes of data, that goes beyond just doing manual programming.Most books in this realm are full of equations and complex code but this book gives a much gentler entry point particularly for biologists, with code snippets users can use to cut and paste, and run on their Linux or MacOSX operating system or cloud instance. It also provides a step by step installation instructions which they can easily follow. Those who are in the field of genome sequencing and already familiar with the procedures of analysis, may also find this book useful in closing some knowledge gaps.High throughput sequencing requires high throughput and high performance computing. This book provides a gentle entry to high throughput sequencing by dealing with simple skills which the average biologist is increasingly required to master. You will find this book a breeze to read, and some suggestions in this book maybe new to you, something you might want to try out.

Beginners Guide To Bioinformatics For High Throughput Sequencing

Beginners Guide To Bioinformatics For High Throughput Sequencing

Author: Tin Wee (Nus, S'pore) Tan, Eric Cheng-yu (Nus, S'pore) Lee Format: Hardback Release Date: 29/11/2018

Biologists find computing bewildering; yet they are expected to be able to process the voluminous data available from the machines they buy and the datasets that has accumulated in genomic databanks worldwide. It is now increasingly difficult for them to avoid dealing with large volumes of data, that goes beyond just doing manual programming.Most books in this realm are full of equations and complex code but this book gives a much gentler entry point particularly for biologists, with code snippets users can use to cut and paste, and run on their Linux or MacOSX operating system or cloud instance. It also provides a step by step installation instructions which they can easily follow. Those who are in the field of genome sequencing and already familiar with the procedures of analysis, may also find this book useful in closing some knowledge gaps.High throughput sequencing requires high throughput and high performance computing. This book provides a gentle entry to high throughput sequencing by dealing with simple skills which the average biologist is increasingly required to master. You will find this book a breeze to read, and some suggestions in this book maybe new to you, something you might want to try out.

Multivariate Analyses of Codon Usage Biases

Multivariate Analyses of Codon Usage Biases

A complete case study with all coding sequences from the bacteria Borrellia burgdorferi illustrates how multivariate analyses reveals evolutionary mechanisms acting at the molecular level. They are either mutationnal (symmetric and asymmetric directionnal mutation pressure) or selective (selection against head-on collisions or linked to gene expressivity or subcellular location).

Smart Health

Smart Health

Author: Hsinchun Chen Format: Paperback / softback Release Date: 26/10/2018

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference for Smart Health, ICSH 2018, held in Wuhan, China, in July 2018.The 14 full papers and 21 short papers presented were carefully reviewed and selected from 49 submissions. They focus on studies on the principles, approaches, models, frameworks, new applications, and effects of using novel information technology to address healthcare problems and improve social welfare. The selected papers are organized into the following topics: smart hospital; online health community; mobile health; medical big data and healthcare machine learning; chronic disease management; and health informatics.

Encyclopedia of Bioinformatics and Computational Biology

Encyclopedia of Bioinformatics and Computational Biology

Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative -omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries.

MATLAB

MATLAB

MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA's 2017 Textbook Excellence Award ( Texty ), guides the reader through both programming and built-in functions to easily exploit MATLAB's extensive capabilities for tackling engineering and scientific problems. Assuming no knowledge of programming, this book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. The fifth edition has been updated to reflect the functionality of the current version of MATLAB (R2018a), including the addition of local functions in scripts, the new string type, coverage of recently introduced functions to import data from web sites, and updates to the Live Editor and App Designer.

An Adolescent's Guide to ME/CFS

An Adolescent's Guide to ME/CFS

Author: Vidhima Shetty Format: Paperback / softback Release Date: 01/08/2018

Current trends in Bioinformatics: An Insight

Current trends in Bioinformatics: An Insight

Author: Gulshan Wadhwa Format: Hardback Release Date: 20/07/2018

This book highlights the latest breakthrough developments in bioinformatics. It presents a series of timely, in-depth reviews, drug clinical trial studies, biodiversity informatics and thematic issues. In addition, it includes insightful reviews on advances in computational molecular/structural biology, which address areas such as computing in biomedicine and genomics, computational proteomics and systems biology, and metabolic pathway engineering. Innovations in these fields have direct impacts on key issues related to healthcare, medicine, genetic disorders, the development of agricultural products, renewable energy, and environmental protection. Written by respected leaders in the field and covering a wide range of topics involving the integration of biology with computer and information science, the book offers an ideal basis for teaching at the undergraduate and graduate levels. It can also be used for self-instruction by research investigators interested in applying bioinformatics-based analytical methods and information technologists working with academic and industrial laboratories.

Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data

Author: Ervin (+1University of Pittsburgh, Pennsylvania, USA) Sejdic Format: Hardback Release Date: 05/07/2018

Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book's material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.