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Medical Content-Based Retrieval for Clinical Decision Support

Medical Content-Based Retrieval for Clinical Decision Support
Second MICCAI International Workshop, MCBR-CDS 2011, Toronto, Canada, September 22, 2011, Revised Selected Papers

by Henning Mueller,Hayit Greenspan,Tanveer Syeda-Mahmood

  • Publisher : Springer
  • Release : 2012-02-21
  • Pages : 153
  • ISBN : 3642284604
  • Language : En, Es, Fr & De
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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
First MICCAI International Workshop, MCBR-CBS 2009, London, UK, September 20, 2009. Revised Selected Papers

by Barbara Caputo,Henning Müller,Tanveer Syeda-Mahmood,James Duncan,Fei Wang,Jayashree Kalpathy-Cramer

  • Publisher : Springer Science & Business Media
  • Release : 2010-02-15
  • Pages : 119
  • ISBN : 3642117686
  • Language : En, Es, Fr & De
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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
Third MICCAI International Workshop, MCBR-CDS 2012, Nice, France, October 1st, 2012, Revised Selected Papers

by Hayit Greenspan,Henning Müller,Tanveer Syeda-Mahmood

  • Publisher : Springer
  • Release : 2013-01-31
  • Pages : 145
  • ISBN : 9783642366772
  • Language : En, Es, Fr & De
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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.

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
Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

by 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
  • Pages : 93
  • ISBN : 3030338509
  • Language : En, Es, Fr & De
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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.

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence

Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence
A Book

by Anitha S. Pillai,Bindu Menon

  • Publisher : Academic Press
  • Release : 2022-02-25
  • Pages : 362
  • ISBN : 0323886264
  • Language : En, Es, Fr & De
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Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence focuses on how the neurosciences can benefit from advances in AI, especially in areas such as medical image analysis for the improved diagnosis of Alzheimer’s disease, early detection of acute neurologic events, prediction of stroke, medical image segmentation for quantitative evaluation of neuroanatomy and vasculature, diagnosis of Alzheimer’s Disease, autism spectrum disorder, and other key neurological disorders. Chapters also focus on how AI can help in predicting stroke recovery, and the use of Machine Learning and AI in personalizing stroke rehabilitation therapy. Other sections delve into Epilepsy and the use of Machine Learning techniques to detect epileptogenic lesions on MRIs and how to understand neural networks. Provides readers with an understanding on the key applications of artificial intelligence and machine learning in the diagnosis and treatment of the most important neurological disorders Integrates recent advancements of artificial intelligence and machine learning to the evaluation of large amounts of clinical data for the early detection of disorders such as Alzheimer’s Disease, autism spectrum disorder, Multiple Sclerosis, headache disorder, Epilepsy, and stroke Provides readers with illustrative examples of how artificial intelligence can be applied to outcome prediction, neurorehabilitation and clinical exams, including a wide range of case studies in predicting and classifying neurological disorders

Artificial Intelligence and Integrated Intelligent Information Systems

Artificial Intelligence and Integrated Intelligent Information Systems
Emerging Technologies and Applications

by Xuan F. Zha

  • Publisher : IGI Global
  • Release : 2007-01-01
  • Pages : 454
  • ISBN : 1599042495
  • Language : En, Es, Fr & De
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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.

Big Data in Multimodal Medical Imaging

Big Data in Multimodal Medical Imaging
A Book

by Ayman El-Baz,Jasjit S. Suri

  • Publisher : CRC Press
  • Release : 2019-11-06
  • Pages : 341
  • ISBN : 1351380729
  • Language : En, Es, Fr & De
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There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.

Signal Processing Techniques for Computational Health Informatics

Signal Processing Techniques for Computational Health Informatics
A Book

by Md Atiqur Rahman Ahad,Mosabber Uddin Ahmed

  • Publisher : Springer Nature
  • Release : 2020-10-07
  • Pages : 334
  • ISBN : 3030549321
  • Language : En, Es, Fr & De
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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.

Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Deep Neural Networks for Multimodal Imaging and Biomedical Applications
A Book

by Suresh, Annamalai,Udendhran, R.,Vimal, S.

  • Publisher : IGI Global
  • Release : 2020-06-26
  • Pages : 294
  • ISBN : 1799835928
  • Language : En, Es, Fr & De
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The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.

Computational Intelligence in Healthcare 4

Computational Intelligence in Healthcare 4
Advanced Methodologies

by Isabelle Bichindaritz,Sachin Vaidya,Ashlesha Jain

  • Publisher : Springer Science & Business Media
  • Release : 2010-09-08
  • Pages : 464
  • ISBN : 3642144632
  • Language : En, Es, Fr & De
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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.

Explainable Artificial Intelligence for Cyber Security

Explainable Artificial Intelligence for Cyber Security
Next Generation Artificial Intelligence

by Mohiuddin Ahmed

  • Publisher : Springer Nature
  • Release : 2022
  • Pages : 129
  • ISBN : 3030966305
  • Language : En, Es, Fr & De
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Biometric and Intelligent Decision Making Support

Biometric and Intelligent Decision Making Support
A Book

by Arturas Kaklauskas

  • Publisher : Springer
  • Release : 2014-12-26
  • Pages : 220
  • ISBN : 3319136593
  • Language : En, Es, Fr & De
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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.

Foundations of Artificial Intelligence in Healthcare and Bioscience

Foundations of Artificial Intelligence in Healthcare and Bioscience
A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians

by Louis J. Catania

  • Publisher : Academic Press
  • Release : 2020-11-25
  • Pages : 558
  • ISBN : 0323860052
  • Language : En, Es, Fr & De
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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

AI 2020: Advances in Artificial Intelligence

AI 2020: Advances in Artificial Intelligence
33rd Australasian Joint Conference, AI 2020, Canberra, ACT, Australia, November 29–30, 2020, Proceedings

by Marcus Gallagher,Nour Moustafa,Erandi Lakshika

  • Publisher : Springer Nature
  • Release : 2020-11-27
  • Pages : 472
  • ISBN : 3030649849
  • Language : En, Es, Fr & De
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This book constitutes the proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence, AI 2020, held in Canberra, ACT, Australia, in November 2020.* The 36 full papers presented in this volume were carefully reviewed and selected from 57 submissions. The paper were organized in topical sections named: applications; evolutionary computation; fairness and ethics; games and swarms; and machine learning. *The conference was held virtually due to the COVID-19 pandemic.

Human and Machine Learning

Human and Machine Learning
Visible, Explainable, Trustworthy and Transparent

by Jianlong Zhou,Fang Chen

  • Publisher : Springer
  • Release : 2018-06-07
  • Pages : 482
  • ISBN : 3319904035
  • Language : En, Es, Fr & De
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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.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Technical Basis and Clinical Applications

by Lei Xing,Maryellen L. Giger,James K. Min

  • Publisher : Academic Press
  • Release : 2020-09-03
  • Pages : 568
  • ISBN : 0128212586
  • Language : En, Es, Fr & De
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Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Artificial Intelligence in Education

Artificial Intelligence in Education
22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14-18, 2021, Proceedings, Part II

by Ido Roll,Danielle S. McNamara,Sergey Sosnovsky,Rose Luckin,Vania Dimitrova

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 492
  • ISBN : 3030782700
  • Language : En, Es, Fr & De
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This two-volume set LNAI 12748 and 12749 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Education, AIED 2021, held in Utrecht, The Netherlands, in June 2021.* The 40 full papers presented together with 76 short papers, 2 panels papers, 4 industry papers, 4 doctoral consortium, and 6 workshop papers were carefully reviewed and selected from 209 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas. *The conference was held virtually due to the COVID-19 pandemic.

Big Data Analytics for Large-Scale Multimedia Search

Big Data Analytics for Large-Scale Multimedia Search
A Book

by Stefanos Vrochidis,Benoit Huet,Edward Y. Chang,Ioannis Kompatsiaris

  • Publisher : John Wiley & Sons
  • Release : 2019-03-18
  • Pages : 376
  • ISBN : 111937698X
  • Language : En, Es, Fr & De
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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.

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry
A Book

by Stephanie K. Ashenden

  • Publisher : Academic Press
  • Release : 2021-04-23
  • Pages : 264
  • ISBN : 0128204494
  • Language : En, Es, Fr & De
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The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide

Artificial Intelligence in Geriatric Mental Health Research and Clinical Care

Artificial Intelligence in Geriatric Mental Health Research and Clinical Care
A Book

by Ellen E. Lee,Andrea Iaboni,Helmet Karim,Ipsit Vahia

  • Publisher : Frontiers Media SA
  • Release : 2022-03-18
  • Pages : 129
  • ISBN : 2889747379
  • Language : En, Es, Fr & De
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