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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!
Conceived as a cross between natural language processing methods and biological sequences in DNA, RNA and protein, biological language model is a new scientific research topic in bioinformatics that has been extensively studied by the authors. The basic theory and applications of this model are presented in this book to serve as an reference for graduate students and researchers.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare.
Microbiomics: Dimensions, Applications, and Translational Implications of Human and Environmental Microbiome Research describes a new, holistic approach to microbiomics. International experts provide in-depth discussion of current research methods for studying human, environmental, viral and fungal microbiomes, as well as the implications of new discoveries for human health, nutrition, disease, cancer research, probiotics and in the food and agricultural industries. Distinct chapters covering culturomics and sub-microbiomes, such as the viriome and mycetobiome, provide an integrative framework for the expansion of microbiomics into new areas of application, as well as crosspollination between research areas. Detailed case studies include the use of microbiomics to develop natural products with antimicrobial properties, microbiomic enhancements in food and beverage technology, microbes for bioprotection and biopreservation, microbial tools to reduce antibiotic resistance, and maintenance and cultivation of human microbial communities.
SAS Data Management for Public Health: An Introduction equips readers with the tools and knowledge they need to prepare public health data in SAS Data Management software for use in analysis. Highly accessible in nature, the book is specifically designed to help students who are new to SAS learn and master the system. The book is organized into 20 lessons. The opening lessons introduce SAS and provide tips and best practices for exploring data. Students are introduced to PROC MEANS, FREQ, UNIVARIATE, and PROC SGPLOT. They learn how to import data; merge, concatenate, and manage variables; perform data cleanup; and recode categorical and continuous variables. Specific lessons address comments, labels, and titles, formatting variables, conditional recoding, DO groups, arrays for recoding, and categorical data analysis. Closing lessons introduce stratified and subpopulation analysis, as well as logistic regression. The book includes an appendix to help students navigate and use SAS Studio. SAS Data Management for Public Health is an ideal resource for standalone courses in which SAS is taught or to complement any biostatistics or epidemiology course where students need to use SAS to analyze their data.