Skip to main content

Building Multimodal Clinical Decision Support Systems Using Artificial Intelligence

In Order to Read Online or Download Building Multimodal Clinical Decision Support Systems Using Artificial Intelligence Full eBooks in PDF, EPUB, Tuebl and Mobi you need to create a Free account. Get any books you like and read everywhere you want. Fast Download Speed ~ Commercial & Ad Free. We cannot guarantee that every book is in the library!

Medical Content Based Retrieval for Clinical Decision Support

Medical Content Based Retrieval for Clinical Decision Support Book
Author : Hayit Greenspan,Henning Müller,Tanveer Syeda-Mahmood
Publisher : Springer
Release : 2013-01-31
ISBN : 9783642366772
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Medical Content Based Retrieval for Clinical Decision Support

Medical Content Based Retrieval for Clinical Decision Support Book
Author : Henning Mueller,Hayit Greenspan,Tanveer Syeda-Mahmood
Publisher : Springer
Release : 2012-02-21
ISBN : 3642284604
Language : En, Es, Fr & De

GET BOOK

Book Description :

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 Book
Author : Barbara Caputo,Henning Müller,Tanveer Syeda-Mahmood,James Duncan,Jayashree Kalpathy-Cramer,Fei Wang
Publisher : Springer Science & Business Media
Release : 2010-02-15
ISBN : 3642117686
Language : En, Es, Fr & De

GET BOOK

Book Description :

The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available.

Medical Content Based Retrieval for Clinical Decision Support

Medical Content Based Retrieval for Clinical Decision Support Book
Author : Hayit Greenspan,Henning Müller,Tanveer Syeda-Mahmood
Publisher : Springer
Release : 2013-02-20
ISBN : 3642366783
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Artificial Intelligence and Integrated Intelligent Information Systems

Artificial Intelligence and Integrated Intelligent Information Systems Book
Author : Xuan F. Zha
Publisher : IGI Global
Release : 2007-01-01
ISBN : 1599042495
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Secondary Analysis of Electronic Health Records

Secondary Analysis of Electronic Health Records Book
Author : MIT Critical Data
Publisher : Springer
Release : 2016-09-09
ISBN : 3319437429
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine Book
Author : Werner Horn,Yuval Shahar,Greger Lindberg,Steen Andreassen,Jeremy Wyatt
Publisher : Springer
Release : 2003-05-21
ISBN : 3540487204
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Signal Processing Techniques for Computational Health Informatics

Signal Processing Techniques for Computational Health Informatics Book
Author : Md Atiqur Rahman Ahad,Mosabber Uddin Ahmed
Publisher : Springer Nature
Release : 2020-10-07
ISBN : 3030549321
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book focuses on signal processing techniques used in computational health informatics. As computational health informatics is the interdisciplinary study of the design, development, adoption and application of information and technology-based innovations, specifically, computational techniques that are relevant in health care, the book covers a comprehensive and representative range of signal processing techniques used in biomedical applications, including: bio-signal origin and dynamics, sensors used for data acquisition, artefact and noise removal techniques, feature extraction techniques in the time, frequency, time–frequency and complexity domain, and image processing techniques in different image modalities. Moreover, it includes an extensive discussion of security and privacy challenges, opportunities and future directions for computational health informatics in the big data age, and addresses the incorporation of recent techniques from the areas of artificial intelligence, deep learning and human–computer interaction. The systematic analysis of the state-of-the-art techniques covered here helps to further our understanding of the physiological processes involved and expandour capabilities in medical diagnosis and prognosis. In closing, the book, the first of its kind, blends state-of-the-art theory and practices of signal processing techniques inthe health informatics domain with real-world case studies building on those theories. As a result, it can be used as a text for health informatics courses to provide medics with cutting-edge signal processing techniques, or to introducehealth professionals who are already serving in this sector to some of the most exciting computational ideas that paved the way for the development of computational health informatics.

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support Book
Author : Kenji Suzuki,Mauricio Reyes,Tanveer Syeda-Mahmood,Ender Konukoglu,Ben Glocker,Roland Wiest,Yaniv Gur,Hayit Greenspan,Anant Madabhushi
Publisher : Springer Nature
Release : 2019-10-24
ISBN : 3030338509
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.

Secondary Analysis of Electronic Health Records

Secondary Analysis of Electronic Health Records Book
Author : MIT Critical Data
Publisher : Springer
Release : 2016-10-02
ISBN : 9783319437408
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Computational Intelligence in Healthcare 4

Computational Intelligence in Healthcare 4 Book
Author : Isabelle Bichindaritz,Sachin Vaidya,Ashlesha Jain
Publisher : Springer Science & Business Media
Release : 2010-09-08
ISBN : 3642144632
Language : En, Es, Fr & De

GET BOOK

Book Description :

Computational Intelligence is comparatively a new field but it has made a tremendous progress in virtually every discipline right from engineering, science, business, m- agement, aviation to healthcare. Computational intelligence already has a solid track-record of applications to healthcare, of which this book is a continuation. We would like to refer the reader to the excellent previous volumes in this series on computational intelligence in heal- care [1-3]. This book is aimed at providing the most recent advances and state of the art in the practical applications of computational intelligence paradigms in healthcare. It - cludes nineteen chapters on using various computational intelligence methods in healthcare such as intelligent agents and case-based reasoning. A number of fielded applications and case studies are presented. Highlighted are in particular novel c- putational approaches to the semantic management of health information such as in the Web 2.0, mobile agents such as in portable devices, learning agents capable of adapting to diverse clinical settings through case-based reasoning, and statistical - proaches in computational intelligence. This book is targeted towards scientists, application engineers, professors, health professionals, professors, and students. Background information on computational intelligence has been provided whenever necessary to facilitate the comprehension of a broad audience including healthcare practitioners.

Biometric and Intelligent Decision Making Support

Biometric and Intelligent Decision Making Support Book
Author : Arturas Kaklauskas
Publisher : Springer
Release : 2014-12-26
ISBN : 3319136593
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Foundations of Artificial Intelligence in Healthcare and Bioscience

Foundations of Artificial Intelligence in Healthcare and Bioscience Book
Author : Louis J. Catania
Publisher : Academic Press
Release : 2020-11-25
ISBN : 0323860052
Language : En, Es, Fr & De

GET BOOK

Book Description :

Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI’s role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care. Provides an illustrated, foundational guide and comprehensive descriptions of what Artificial Intelligence is and how it functions Integrates a comprehensive discussion of AI applications in the business of health care Presents in-depth clinical and AI-related discussions on diagnostic medicine, therapeutic medicine, and prevalent disease categories with an emphasis on immunology and genetics, the two categories most influenced by AI Includes comprehensive coverage of a variety of AI treatment applications, including medical/pharmaceutical care, nursing care, stem cell therapies, robotics, and 10 common disease categories with AI applications

Big Data Analytics for Large Scale Multimedia Search

Big Data Analytics for Large Scale Multimedia Search Book
Author : Stefanos Vrochidis,Benoit Huet,Edward Y. Chang,Ioannis Kompatsiaris
Publisher : John Wiley & Sons
Release : 2019-03-18
ISBN : 111937698X
Language : En, Es, Fr & De

GET BOOK

Book Description :

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.

Artificial Intelligence in Education

Artificial Intelligence in Education Book
Author : Ido Roll
Publisher : Springer Nature
Release : 2021-10-19
ISBN : 3030782700
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Artificial Intelligence in Education book written by Ido Roll, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Programs and Services

Programs and Services Book
Author : National Library of Medicine (U.S.)
Publisher : Unknown
Release : 2021-10-19
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Programs and Services book written by National Library of Medicine (U.S.), available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

National Library of Medicine Programs and Services

National Library of Medicine Programs and Services Book
Author : National Library of Medicine (U.S.).
Publisher : Unknown
Release : 1984
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download National Library of Medicine Programs and Services book written by National Library of Medicine (U.S.)., available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Advances in Artificial Intelligence

Advances in Artificial Intelligence Book
Author : br Ibero-American Conference on Artificial Intelligence 2000 Atibaia,Maria C. Monard,Ibero-American Conference on Artificial Intelligence
Publisher : Springer Science & Business Media
Release : 2000-10-25
ISBN : 354041276X
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book constitutes the refereed joint proceedings of the 7th Ibero-American Conference on AI and the 15th Brazilian Symposium on AI, IBERAMIA-SBIA 2000, held in Atibaia, Brazil in November 2000. The 48 revised full papers presented together with two invited contributions were carefully reviewed and selected from a total of 156 submissions. The papers are organized in topical sections on knowledge engineering and case-based reasoning, planning and scheduling, distributed AI and multi-agent systems, AI in education and intelligent tutoring systems, knowledge representation and reasoning, machine learning and knowledge acquisition, knowledge discovery and data mining, natural language processing, robotics, computer vision, uncertainty and fuzzy systems, and genetic algorithms and neural networks.

Human and Machine Learning

Human and Machine Learning Book
Author : Jianlong Zhou,Fang Chen
Publisher : Springer
Release : 2018-06-07
ISBN : 3319904035
Language : En, Es, Fr & De

GET BOOK

Book Description :

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications. This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making. This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially benefit researchers in areas like artificial intelligence, decision support systems and human-computer interaction.