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Big data analytics and machine intelligence in biomedical and health informatics : Concepts, methodologies, tools and applications
Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. Covers the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).
AI in clinical practice : A guide to artificial intelligence and digital medicine
Explains how artificial intelligence is applied to medicine, illustrating not only its enormous potential but also ancillary issues and the limits and risks inherent in its use on a large scale. The book focuses on the intersection between medicine and AI and its implications on the impact of human health care delivery. Topics discussed include wearable devices, health data, Internet of Things, virtual reality, robotic assistance system, and digital intelligence in the health sector. Additionally, sections discuss diagnostics and decision-making systems and machine/deep learning in clinical setting.
Java for Bioinformatics and Biomedical Applications
Illustrates how individual bioinformatics applications (such as BLAST and Genscan) can be stitched together into a pipeline so that users can direct the output of one tool (for example, gene predictions using Genscan) to perform further analysis (say, homology searching using BLAST).
Computational biology in drug discovery and repurposing
Takes an in-depth look at the emerging and prospective field of computational biology and bioinformatics, which possesses the ability to analyze large accumulated biological data collected from sequence analysis of proteins and genes and cell population with an aim to make new predictions pertaining to drug discovery and new biology. The book explains the basic methodology associated with a bioinformatics and computational approach in drug designing. It then goes on to cover the implementation of computational programming, bioinformatics, pharmacophore modeling, biotechnological techniques, and pharmaceutical chemistry in designing drugs. The major advantage of intervention of computer language or programming is to cut down the number of steps and costs in the field of drug designing, reducing the repeating steps and saving time in screening the potent component for drug or vaccine designin
Clinical decision support systems : Theory and practice
Writes the editor, "If used properly, CDSS have the potential to change the way medicine has been taught and practiced." As clinical decision support systems (CDSS) gain an increasingly central role in the delivery of high quality health care, it becomes more important for the health care community to understand their use. This text is designed as a resource for practicing clinicians, informaticians, teachers and students alike, and provides the most current, comprehensive look a the development and evaluation of clinical decision support systems.
Biomedical Informatics : Computer Applications in Health Care and Biomedicine
This series is directed to healthcare professionals who are leading the transformation of health care by using information and knowledge. Launched in 1988 as Computers in Health Care, the series offers a broad range of titles: some addressed to specific prof- sions such as nursing, medicine, and health administration; others to special areas of practice such as trauma and radiology.
Artificial intelligence in drug design
Looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future.
AI in clinical medicine : A practical guide for healthcare professionals
A Practical Guide for Healthcare Professionals is the definitive reference book for the emerging and exciting use of AI throughout clinical medicine. AI in Clinical Medicine: A Practical Guide for Healthcare Professionals is divided into four sections. Section 1 provides readers with the basic vocabulary that they require, a framework for AI, and highlights the importance of robust AI training for physicians. Section 2 reviews foundational ideas and concepts, including the history of AI. Section 3 explores how AI is applied to specific disciplines. Section 4 describes emerging trends, and applications of AI in medicine in the future.
Advanced soft electronics in biomedical engineering : materials, manufactures, and applications
Presents the latest advances in soft electronics in biomedical engineering and its potential applications in various biomedical fields. Provide comprehensive coverage of how soft electronics are used in diagnostics and monitoring, medical therapy, neural engineering, and wearable and implantable systems. In particular, some emerging research areas such as advanced soft robotics, fiber sensing technologies, and power optimization strategies are explored. In addition, the book highlights international standardization activities in wearable technologies and implantable bioelectronics.
Biomedical data mining for information retrieval : Methodologies, techniques, and applications
Discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. 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 healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally.
Biological and medical data analysis ; Vol. 3745 ; 6th International symposium, ISBMDA 2005, Aveiro, Portugal, November 10-11, 2005, Proceedings
The 6th International Symposium on Biological and Medical Data Analysisaimed to become a place where researchersinvolved in these diverse but increas-ingly complementary areas could meet topresent and discuss their scientificresults.The papers in this volume discuss issues from statistical models to archi-tectures and applications to bioinformatics and biomedicine. They cover bothpractical experience and novel research ideas and concepts.
Artificial intelligence in medicine
Provides a structured and analytical guide to the use of artificial intelligence in medicine. Covering all areas within medicine, the chapters give a systemic review of the history, scientific foundations, present advances, potential trends, and future challenges of artificial intelligence within a healthcare setting.
3rd Kuala Lumpur International Conference on Biomedical Engineering 2006 ; Biomed 2006, 11-14 December 2006, Kuala Lumpur, Malaysia
The Kuala Lumpur International Conference on Biomedical Engineering (Biomed 2006) was held from 11 to 14 December 2006 at the Palace of the Golden Horses, Kuala Lumpur, Malaysia. This international conference was jointly organised by the Department of Biomedical Engineering, University of Malaya, Malaysia; Department of Biomedical Engineering, Inje University, Korea; and Malaysian Society of Medical and Biological Engineering. The papers presented at Biomed 2006 cover the following areas: artificial intelligence, biological effects of non-ionising electromagnetic fields, biomaterials, biomechanics, biomedical sensors, biomedical signal analysis, biotechnology, clinical engineering, human performance engineering, imaging, medical informatics, medical instruments and devices, physiological modelling, simulation, and control, prostheses and artificial organs, regulations and organisations, rehabilitation engineering, telemedicine, tissue engineering, and virtual reality in medicine.
