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All About Bioinformatics
All About Bioinformatics: From Beginner to Expert provides readers with an overview of the fundamentals and advances in the _x001F_field of bioinformatics, as well as some future directions. Each chapter is didactically organized and includes introduction, applications, tools, and future directions to cover the topics thoroughly. The book covers both traditional topics such as biological databases, algorithms, genetic variations, static methods, and structural bioinformatics, as well as contemporary advanced topics such as high-throughput technologies, drug informatics, system and network biology, and machine learning. It is a valuable resource for researchers and graduate students who are i...
Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing
This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and it...
Genomics Data Analysis for Crop Improvement
This book addresses complex problems associated with crop improvement programs, using a wide range of programming solutions, for genomics data handling and sustainable agriculture. It describes important concepts in genomics data analysis and sequence-based mapping approaches along with references. The book contains 16 chapters on recent developments in several methods of genomic data analysis for crop improvements and sustainable agriculture, all authored by eminent researchers who are experts in their fields. These chapters focus on applications of a wide range of key bioinformatics topics, including assembly, annotation, and visualization of next-generation sequencing (NGS) data; expressi...
Anticancer Plants: Mechanisms and Molecular Interactions
This book summarizes the application of plant derived anticancer compounds as chemopreventives to treat several cancer types, focusing on the molecular mechanisms of action of phytocompounds and providing an overview of the basic processes at the cellular and molecular level that are involved in the progression of the cancer and can be employed in targeted preventive therapies. In addition, it highlights the development of novel anticancer drugs from plant sources using bioinformatics approaches. The compiled chapter data aids readers understanding of issues related to bioavailability, toxic effects and mechanisms of action of phytocompounds, and helps them identify the leads and utilize the...
Biomedical Data Mining for Information Retrieval
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of hea...
Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021)
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.
Predictive Analytics of Psychological Disorders in Healthcare
This book discusses an interdisciplinary field which combines two major domains: healthcare and data analytics. It presents research studies by experts helping to fight discontent, distress, anxiety and unrealized potential by using mathematical models, machine learning, artificial intelligence, etc. and take preventive measures beforehand. Psychological disorders and biological abnormalities are significantly related with the applications of cognitive illnesses which has increased significantly in contemporary years and needs rapid investigation. The research content of this book is helpful for psychological undergraduates, health workers and their trainees, therapists, medical psychologists, and nurses.
Internet of Things and Machine Learning for Type I and Type II Diabetes
Internet of Things and Machine Learning for?Type I and Type II Diabetes: Use Cases provides a medium of exchange of expertise and addresses the concerns, needs, and problems associated with Type I and Type II diabetes. Expert contributions come from researchers across biomedical, data mining, and deep learning. This is an essential resource for both the AI and Biomedical research community, crossing various sectors for broad coverage of the concepts, themes, and instrumentalities of this important and evolving area. Coverage includes IoT, AI, Deep Learning, Machine Learning and Big Data Analytics for diabetes and health informatics. - Integrates many Machine learning techniques in biomedical domain to detect various types of diabetes to utilizing large volumes of available diabetes-related data for extracting knowledge - It integrates data mining and IoT techniques to monitor diabetes patients using their medical records (HER) and administrative data - Includes clinical applications to highlight contemporary use of these machine learning algorithms and artificial intelligence-driven models beyond research settings
Deep Learning Techniques for Biomedical and Health Informatics
This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the ...
Pharmaceutical Sciences: Breakthroughs in Research and Practice
The delivery of optimal pharmaceutical services to patients is a pivotal concern in the healthcare field. By examining current trends and techniques in the industry, processes can be maintained and improved. Pharmaceutical Sciences: Breakthroughs in Research and Practice provides comprehensive coverage of the latest innovations and advancements for pharmaceutical applications. Focusing on emerging drug development techniques and drug delivery for improved health outcomes, this book is ideally designed for medical professionals, pharmacists, researchers, academics, and upper-level students within the growing pharmaceutical industry.
