November 28, 2020

Download Ebook Free Building Multimodal Clinical Decision Support Systems Using Artificial Intelligence

Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
Author : Henning Mueller,Hayit Greenspan,Tanveer Syeda-Mahmood
Publisher : Springer
Release Date : 2012-02-21
Category : Computers
Total pages :153
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This book constitutes the refereed proceedings of the Second MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2011, held in Toronto, Canada, in September 2011. The 11 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 17 submissions. The papers are divided on several topics on medical image retrieval with textual approaches, visual word based approaches, applications and multidimensional retrieval.

Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
Author : Henning Müller,Tanveer Syeda-Mahmood,James Duncan,Fei Wang,Jayashree Kalpathy-Cramer
Publisher : Springer
Release Date : 2010-02-04
Category : Computers
Total pages :121
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This book constitutes the refereed proceedings of the first MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR_CBS 2009, held in London, UK, in September 2009. The 10 revised full papers were carefully reviewed and selected from numerous submissions. The papers are divide on several topics on medical image retrieval, clinical decision making and multimodal fusion.

Artificial Intelligence and Integrated Intelligent Information Systems: Emerging Technologies and Applications

Artificial Intelligence and Integrated Intelligent Information Systems: Emerging Technologies and Applications
Author : Zha, Xuan
Publisher : IGI Global
Release Date : 2006-10-31
Category : Computers
Total pages :478
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Researchers in the evolving fields of artificial intelligence and information systems are constantly presented with new challenges. Artificial Intelligence and Integrated Intelligent Information Systems: Emerging Technologies and Applications provides both researchers and professionals with the latest knowledge applied to customized logic systems, agent-based approaches to modeling, and human-based models. Artificial Intelligence and Integrated Intelligent Information Systems: Emerging Technologies and Applications presents the recent advances in multi-mobile agent systems, the product development process, fuzzy logic systems, neural networks, and ambient intelligent environments among many other innovations in this exciting field.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author : Werner Horn,Yuval Shahar,Greger Lindberg,Steen Andreassen,Jeremy Wyatt
Publisher : Springer
Release Date : 2003-05-21
Category : Medical
Total pages :462
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This book constitutes the refereed proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, AIMDM'99, held in Aalborg, Denmark, in June 1999. The 27 full papers and 19 short papers presented in the book together with four invited papers were selected from 90 submissions. The papers are organized in topical sections on guidelines and protocols; decision support systems, knowledge-based systems, and cooperative systems; model-based systems; neural nets and causal probabilistic networks; knowledge representation; temporal reasoning; machine learning; natural language processing; and image processing and computer aided design.

Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
Author : Hayit Greenspan,Henning Mèuller,Tanveer Syeda-Mahmood
Publisher : Unknown
Release Date : 2013
Category : Computer vision
Total pages :145
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This book constitutes the refereed proceedings of the Third MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CBS 2012, held in Nice, France, in October 2012. The 10 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 15 submissions. The papers are divided on several topics on image analysis of visual or multimodal medical data (X-ray, MRI, CT, echo videos, time series data), machine learning of disease correlations in visual or multimodal data, algorithms for indexing and retrieval of data from visual or multimodal medical databases, disease model-building and clinical decision support systems based on visual or multimodal analysis, algorithms for medical image retrieval or classification, systems of retrieval or classification using the ImageCLEF collection.

Reinventing Clinical Decision Support

Reinventing Clinical Decision Support
Author : Paul Cerrato,John Halamka
Publisher : Taylor & Francis
Release Date : 2020-01-15
Category : Business & Economics
Total pages :166
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This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
Author : M. Jorge Cardoso,Tal Arbel,Gustavo Carneiro,Tanveer Syeda-Mahmood,João Manuel R.S. Tavares,Mehdi Moradi,Andrew Bradley,Hayit Greenspan,João Paulo Papa,Anant Madabhushi,Jacinto C. Nascimento,Jaime S. Cardoso,Vasileios Belagiannis,Zhi Lu
Publisher : Springer
Release Date : 2017-09-07
Category : Computers
Total pages :385
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This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.

Intelligent Human Systems Integration 2019

Intelligent Human Systems Integration 2019
Author : Waldemar Karwowski,Tareq Ahram
Publisher : Springer
Release Date : 2019-01-05
Category : Technology & Engineering
Total pages :925
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This book presents cutting-edge research on innovative human systems integration and human–machine interaction, with an emphasis on artificial intelligence and automation, as well as computational modeling and simulation. It covers a wide range of applications in the area of design, construction and operation of products, systems and services, including lifecycle development and human–technology interaction. The book describes advanced methodologies and tools for evaluating and improving interface usability, new models, and case studies and best practices in virtual, augmented and mixed reality systems, with a special focus on dynamic environments. It also discusses various factors concerning the human user, hardware, and artificial intelligence software. Based on the proceedings of the 2nd International Conference on Intelligent Human Systems Integration (IHSI 2019), held on February 7–10, 2019, in San Diego, California, USA, the book also examines the forces that are currently shaping the nature of computing and cognitive systems, such as the need to reduce hardware costs; the importance of infusing intelligence and automation; the trend toward hardware miniaturization and power reduction; the need for a better assimilation of computation in the environment; and social concerns regarding access to computers and systems for people with special needs. It offers a timely survey and a practice-oriented reference guide for policy- and decision-makers, human factors engineers, systems developers and users alike.

Secondary Analysis of Electronic Health Records

Secondary Analysis of Electronic Health Records
Author : MIT Critical Data
Publisher : Springer
Release Date : 2016-09-09
Category : Medical
Total pages :427
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This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

Innovation in Medicine and Healthcare Systems, and Multimedia

Innovation in Medicine and Healthcare Systems, and Multimedia
Author : Yen-Wei Chen,Alfred Zimmermann,Robert J. Howlett,Lakhmi C. Jain
Publisher : Springer
Release Date : 2019-06-05
Category : Technology & Engineering
Total pages :619
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This book contains the proceedings of the KES International conferences on Innovation in Medicine and Healthcare (KES-InMed-19) and Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-19), held on 17–19 June 2019 and co-located in St. Julians, on the island of Malta, as part of the KES Smart Digital Futures 2019 multi-theme conference. The major areas covered by KES-InMed-19 include: Digital IT Architecture in Healthcare; Advanced ICT for Medical and Healthcare; Biomedical Engineering, Trends, Research and Technologies and Healthcare Support System. The major areas covered by KES-IIMSS-19 were: Interactive Technologies; Artificial Intelligence and Data Analytics; Intelligent Services and Architectures and Applications. This book is of use to researchers in these vibrant areas, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields.

National Library of Medicine programs and services. 1990

National Library of Medicine programs and services. 1990
Author : Anonim
Publisher : Unknown
Release Date : 1972
Category :
Total pages :129
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Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications

Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications
Author : Wang, John
Publisher : IGI Global
Release Date : 2008-05-31
Category : Technology & Engineering
Total pages :4092
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In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.

Biometric and Intelligent Decision Making Support

Biometric and Intelligent Decision Making Support
Author : Arturas Kaklauskas
Publisher : Springer
Release Date : 2014-12-26
Category : Computers
Total pages :220
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This book presents different methods for analyzing the body language (movement, position, use of personal space, silences, pauses and tone, the eyes, pupil dilation or constriction, smiles, body temperature and the like) for better understanding people’s needs and actions, including biometric data gathering and reading. Different studies described in this book indicate that sufficiently much data, information and knowledge can be gained by utilizing biometric technologies. This is the first, wide-ranging book that is devoted completely to the area of intelligent decision support systems, biometrics technologies and their integrations. This book is designated for scholars, practitioners and doctoral and master’s degree students in various areas and those who are interested in the latest biometric and intelligent decision making support problems and means for their resolutions, biometric and intelligent decision making support systems and the theory and practice of their integration and the opportunities for the practical use of biometric and intelligent decision making support.

Artificial Intelligence In Medicine

Artificial Intelligence In Medicine
Author : Peter Szolovits
Publisher : Routledge
Release Date : 2019-03-13
Category : Social Science
Total pages :226
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This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care. An introductory chapter describes the historical and technical foundations of the work and provides an overview of the current state of the art and research directions. The authors then describe four prototype computer programs that tackle difficult clinical problems in a manner similar to that of an expert physician. The programs presented are internist, a diagnostic aid that combines a large database of disease/manifestation associations with techniques for problem formulation; expert and the Glaucoma Program which use physiological models for the diagnosis and treatment of eye disease; mycin, a rule-based program for diagnosis and therapy selection for infectious diseases; and the Digitalis Therapy Advisor, which aids the physician in prescribing the right dose of the drug digitalis and also explains its actions.

Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
Author : Dr. Basant Agarwal,Valentina E. Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
Publisher : Academic Press
Release Date : 2020-01-14
Category : Science
Total pages :367
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Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis