Methods, Models, and Computation for Medical Informatics PDF Download

Author: Gangopadhyay, Aryya
Publisher: IGI Global
ISBN: 1466626844
Category : Medical
Languages : en
Pages : 345

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Book Description
Regular developments in technology continue to influence the medical and healthcare fields as they interact with information and computer sciences by methods of acquisition and the storage and retrieval of information. Methods, Models, and Computation for Medical Informatics is a comprehensive collection of research on computational capabilities, prototypes, and algorithms, as well as application in the areas of nursing, clinical care, public health, biomedical research, and much more. This book provides a better understanding of the models and methods used in the field of medicine for researchers, practitioners, and medical professionals alike.

Author: Jules J. Berman
Publisher: CRC Press
ISBN: 9781439841846
Category : Mathematics
Languages : en
Pages : 413

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Book Description
Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implemented with open source programming languages, you can fully utilize the medical information contained in clini

Author: Indra Neil Sarkar
Publisher: Academic Press
ISBN: 0124016847
Category : Computers
Languages : en
Pages : 589

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Book Description
Beginning with a survey of fundamental concepts associated with data integration, knowledge representation, and hypothesis generation from heterogeneous data sets, Methods in Biomedical Informatics provides a practical survey of methodologies used in biological, clinical, and public health contexts. These concepts provide the foundation for more advanced topics like information retrieval, natural language processing, Bayesian modeling, and learning classifier systems. The survey of topics then concludes with an exposition of essential methods associated with engineering, personalized medicine, and linking of genomic and clinical data. Within an overall context of the scientific method, Methods in Biomedical Informatics provides a practical coverage of topics that is specifically designed for: (1) domain experts seeking an understanding of biomedical informatics approaches for addressing specific methodological needs; or (2) biomedical informaticians seeking an approachable overview of methodologies that can be used in scenarios germane to biomedical research. Contributors represent leading biomedical informatics experts: individuals who have demonstrated effective use of biomedical informatics methodologies in the real-world, high-quality biomedical applications Material is presented as a balance between foundational coverage of core topics in biomedical informatics with practical "in-the-trenches" scenarios. Contains appendices that function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4) Web Services.

Author: Tan, Joseph
Publisher: IGI Global
ISBN: 1605660515
Category : Education
Languages : en
Pages : 2772

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Book Description
Provides a collection of medical IT research in topics such as clinical knowledge management, medical informatics, mobile health and service delivery, and gene expression.

Author: Dirk Husmeier
Publisher: Springer Science & Business Media
ISBN: 1846281199
Category : Computers
Languages : en
Pages : 511

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Book Description
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Author: Carmela Comito
Publisher: Springer Nature
ISBN: 3030911810
Category : Technology & Engineering
Languages : en
Pages : 188

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Book Description
The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.

Author: Ripon Patgiri
Publisher: Springer Nature
ISBN: 9811597359
Category : Technology & Engineering
Languages : en
Pages : 384

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Book Description
This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help of computing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.

Author: Vimla L. Patel
Publisher: Springer
ISBN: 3319172727
Category : Medical
Languages : en
Pages : 344

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Book Description
The book reports on the current state on HCI in biomedicine and health care, focusing on the role of human factors, patient safety well as methodological underpinnings of HCI theories and its application for biomedical informatics. Theories, models and frameworks for human-computer interaction (HCI) have been recognized as key contributors for the design, development and use of computer-based systems. In the clinical domain, key themes that litter the research landscape of health information technology (HIT) are usability, decision support and clinical workflow – all of which are affected directly or indirectly by the nature of HCI. While the implications of HCI principles for the design of HIT are acknowledged, the adoption of the tools and techniques among clinicians, informatics researchers and developers of HIT are limited. There is a general consensus that HIT has not realized its potential as a tool to facilitate clinical decision-making, the coordination of care and improves patient safety. Embracing sound principles of iterative design can yield significant dividends. It can also enhance practitioner’s abilities to meet “meaningful use” requirements. The purpose of the book is two-fold: to address key gaps on the applicability of theories, models and evaluation frameworks of HCI and human factors for research in biomedical informatics. It highlights the state of the art, drawing from the current research in HCI. Second, it also serves as a graduate level textbook highlighting key topics in HCI relevant for biomedical informatics, computer science and social science students working in the healthcare domain. For instructional purposes, the book provides additional information and a set of questions for interactive class discussion for each section. The purpose of these questions is to encourage students to apply the learned concepts to real world healthcare problems.​

Author: Arvind Kumar Bansal
Publisher: CRC Press
ISBN: 1000761592
Category : Medical
Languages : en
Pages : 664

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Book Description
This class-tested textbook is designed for a semester-long graduate or senior undergraduate course on Computational Health Informatics. The focus of the book is on computational techniques that are widely used in health data analysis and health informatics and it integrates computer science and clinical perspectives. This book prepares computer science students for careers in computational health informatics and medical data analysis. Features Integrates computer science and clinical perspectives Describes various statistical and artificial intelligence techniques, including machine learning techniques such as clustering of temporal data, regression analysis, neural networks, HMM, decision trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques such as multidimensional and multimedia data representation and retrieval, ontology, patient-data deidentification, temporal data analysis, heterogeneous databases, medical image analysis and transmission, biosignal analysis, pervasive healthcare, automated text-analysis, health-vocabulary knowledgebases and medical information-exchange Includes bioinformatics and pharmacokinetics techniques and their applications to vaccine and drug development

Author: Sujata Dash
Publisher: John Wiley & Sons
ISBN: 1119711266
Category : Computers
Languages : en
Pages : 450

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Book Description
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 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. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.