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Big Data In Psychiatry And Neurology

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Big Data in Psychiatry and Neurology

Big Data in Psychiatry and Neurology Book
Author : Ahmed A. Moustafa
Publisher : Academic Press
Release : 2021-06-24
ISBN : 0128230029
Language : En, Es, Fr & De

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Book Description :

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer’s disease and Parkinson’s disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders Analyzes methods in using big data to treat psychiatric and neurological disorders Describes the role machine learning can play in the analysis of big data Demonstrates the various methods of gathering big data in medicine Reviews how to apply big data to genetics

Personalized Psychiatry

Personalized Psychiatry Book
Author : Ives Cavalcante Passos,Benson Mwangi,Flávio Kapczinski
Publisher : Springer
Release : 2019-02-22
ISBN : 9783030035525
Language : En, Es, Fr & De

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Book Description :

This book integrates the concepts of big data analytics into mental health practice and research. Mental disorders represent a public health challenge of staggering proportions. According to the most recent Global Burden of Disease study, psychiatric disorders constitute the leading cause of years lost to disability. The high morbidity and mortality related to these conditions are proportional to the potential for overall health gains if mental disorders can be more effectively diagnosed and treated. In order to fill these gaps, analysis in science, industry, and government seeks to use big data for a variety of problems, including clinical outcomes and diagnosis in psychiatry. Multiple mental healthcare providers and research laboratories are increasingly using large data sets to fulfill their mission. Briefly, big data is characterized by high volume, high velocity, variety and veracity of information, and to be useful it must be analyzed, interpreted, and acted upon. As such, focus has to shift to new analytical tools from the field of machine learning that will be critical for anyone practicing medicine, psychiatry and behavioral sciences in the 21st century. Big data analytics is gaining traction in psychiatric research, being used to provide predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. Personalized Psychiatry – Big Data Analytics in Mental Health provides a unique opportunity to showcase innovative solutions tackling complex problems in mental health using big data and machine learning. It represents an interesting platform to work with key opinion leaders to document current achievements, introduce new concepts as well as project the future role of big data and machine learning in mental health.

Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data Book
Author : Ervin Sejdic,Tiago H. Falk
Publisher : CRC Press
Release : 2018-07-04
ISBN : 149877346X
Language : En, Es, Fr & De

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Book Description :

Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.

Recent Advances in Big Data and Deep Learning

Recent Advances in Big Data and Deep Learning Book
Author : Luca Oneto,Nicolò Navarin,Alessandro Sperduti,Davide Anguita
Publisher : Springer
Release : 2019-04-02
ISBN : 3030168417
Language : En, Es, Fr & De

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Book Description :

This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.

Intelligent Methods and Big Data in Industrial Applications

Intelligent Methods and Big Data in Industrial Applications Book
Author : Robert Bembenik,Łukasz Skonieczny,Grzegorz Protaziuk,Marzena Kryszkiewicz,Henryk Rybinski
Publisher : Springer
Release : 2018-05-18
ISBN : 3319776045
Language : En, Es, Fr & De

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Book Description :

The inspiration for this book came from the Industrial Session of the ISMIS 2017 Conference in Warsaw. It covers numerous applications of intelligent technologies in various branches of the industry. Intelligent computational methods and big data foster innovation and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research findings to create new designs and products. As such, the contributions cover solutions to the problems experienced by practitioners in the areas of artificial intelligence, complex systems, data mining, medical applications and bioinformatics, as well as multimedia- and text processing. Further, the book shows new directions for cooperation between science and industry and facilitates efficient transfer of knowledge in the area of intelligent information systems.

Ethical Reasoning in Big Data

Ethical Reasoning in Big Data Book
Author : Jeff Collmann,Sorin Adam Matei
Publisher : Springer
Release : 2016-04-22
ISBN : 3319284223
Language : En, Es, Fr & De

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Book Description :

This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public’s trust in the abilities of particular scientists and scientific institutions constitutes one of this book’s major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to harvest – sometimes implicitly – a wealth of human genomic, biological, behavioral, economic, political, and social data for the purposes of scientific research as well as commerce, government affairs, and social interaction. What type of ethical dilemmas did such changes generate? How should scientists collect, manipulate, and disseminate this information? The effects of this revolution and its ethical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in action, the book offers a range of observations, lessons learned, reasoning tools, and suggestions for institutional practice to promote responsible big data research on human affairs. It caters to a broad audience of educators, researchers, and practitioners. Educators can use the volume in courses related to big data handling and processing. Researchers can use it for designing new methods of collecting, processing, and disseminating big data, whether in raw form or as analysis results. Lastly, practitioners can use it to steer future tools or procedures for handling big data. As this topic represents an area of great interest that still remains largely undeveloped, this book is sure to attract significant interest by filling an obvious gap in currently available literature.

Intelligence Science and Big Data Engineering

Intelligence Science and Big Data Engineering Book
Author : Yi Sun,Huchuan Lu,Lihe Zhang,Jian Yang,Hua Huang
Publisher : Springer
Release : 2017-09-14
ISBN : 3319677772
Language : En, Es, Fr & De

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Book Description :

This book constitutes the proceedings of the 7th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017, held in Dalian, China, in September 2017.The 48 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 121 submissions. They deal with statistics and learning; deep neural networks; faces and people; objects; classification and clustering; imaging; biomedical signal processing; and recommendation.

The Ethics of Biomedical Big Data

The Ethics of Biomedical Big Data Book
Author : Brent Daniel Mittelstadt,Luciano Floridi
Publisher : Springer
Release : 2016-08-03
ISBN : 3319335251
Language : En, Es, Fr & De

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Book Description :

This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.

Neuromarketing and Big Data Analytics for Strategic Consumer Engagement Emerging Research and Opportunities

Neuromarketing and Big Data Analytics for Strategic Consumer Engagement  Emerging Research and Opportunities Book
Author : de Sousa, Joana Coutinho
Publisher : IGI Global
Release : 2017-12-30
ISBN : 1522548351
Language : En, Es, Fr & De

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Book Description :

A new sub-area of marketing is emerging called neuromarketing. It combines psychology, neuroscience, and economics with the study of consumer motivations. This is leading to the creation of new technological approaches that enable companies to read the customer's mind and tailor marketing practices, products, and services. Neuromarketing and Big Data Analytics for Strategic Consumer Engagement: Emerging Research and Opportunities provides emerging information on the issues involved in the field of neuromarketing, including models, technologies, and the methodology of this field. Highlighting the intricacies of neuroscience, biometrics, multimedia technology, marketing strategy, and big data management, this book is an ideal resource for researchers, neuroscientists, marketers, suppliers, customers, and investors seeking current research on the integration of new neuromarketing trends and technologies.

Intelligence Science and Big Data Engineering

Intelligence Science and Big Data Engineering Book
Author : Changyin Sun,Fang Fang,Zhi-Hua Zhou,Wankou Yang,Zhiyong Liu
Publisher : Springer
Release : 2013-11-18
ISBN : 3642420575
Language : En, Es, Fr & De

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Book Description :

This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013, held in Beijing, China, in July/August 2013. The 111 papers presented were carefully peer-reviewed and selected from 390 submissions. Topics covered include information theoretic and Bayesian approaches; probabilistic graphical models; pattern recognition and computer vision; signal processing and image processing; machine learning and computational intelligence; neural networks and neuro-informatics; statistical inference and uncertainty reasoning; bioinformatics and computational biology and speech recognition and natural language processing.

Data Intensive Computing Applications for Big Data

Data Intensive Computing Applications for Big Data Book
Author : M. Mittal,V.E. Balas,D.J. Hemanth
Publisher : IOS Press
Release : 2018-01-31
ISBN : 1614998140
Language : En, Es, Fr & De

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Book Description :

The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Healthcare and Big Data Management

Healthcare and Big Data Management Book
Author : Bairong Shen
Publisher : Springer
Release : 2017-10-20
ISBN : 981106041X
Language : En, Es, Fr & De

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Book Description :

The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare; physiological and gut microbiota – data collection and analysis; big data standardization and ontology; and personal data privacy and systems level modeling in the healthcare context. The book offers a valuable resource for biomedical informaticians, clinicians, health practitioners and researchers alike.

Compulsory Interventions in Psychiatry an Overview on the Current Situation and Recommendations for Prevention and Adequate Use

Compulsory Interventions in Psychiatry  an Overview on the Current Situation and Recommendations for Prevention and Adequate Use Book
Author : Christian Huber,Andres Ricardo Schneeberger
Publisher : Frontiers Media SA
Release : 2021-02-24
ISBN : 2889665038
Language : En, Es, Fr & De

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Book Description :

Download Compulsory Interventions in Psychiatry an Overview on the Current Situation and Recommendations for Prevention and Adequate Use book written by Christian Huber,Andres Ricardo Schneeberger, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Medical Computer Vision Algorithms for Big Data

Medical Computer Vision  Algorithms for Big Data Book
Author : Bjoern Menze,Georg Langs,Albert Montillo,Michael Kelm,Henning Müller,Shaoting Zhang,Weidong Cai,Dimitris Metaxas
Publisher : Springer
Release : 2016-07-29
ISBN : 331942016X
Language : En, Es, Fr & De

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Book Description :

This book constitutes the thoroughly refereed prost-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCS 2015, held in Munich, Germany, in October 2015, held in conjunction with the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015. The workshop shows well the current trends and tendencies in medical computer vision and how the techniques can be used in clinical work and on large data sets. It is organized in the following sections: predicting disease; atlas exploitation and avoidance; machine learning based analyses; advanced methods for image analysis; poster sessions. The 10 full, 5 short, 1 invited papers and one overview paper presented in this volume were carefully reviewed and selected from 22 submissions.

Big Data in Multimodal Medical Imaging

Big Data in Multimodal Medical Imaging Book
Author : Ayman El-Baz,Jasjit S. Suri
Publisher : CRC Press
Release : 2019-11-05
ISBN : 1351380737
Language : En, Es, Fr & De

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Book Description :

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.

Machine Learning

Machine Learning Book
Author : Andrea Mechelli,Sandra Vieira
Publisher : Academic Press
Release : 2019-11-14
ISBN : 0128157402
Language : En, Es, Fr & De

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Book Description :

Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. Provides a non-technical introduction to machine learning and applications to brain disorders Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches Covers the main methodological challenges in the application of machine learning to brain disorders Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python

Early Detection of Neurological Disorders Using Machine Learning Systems

Early Detection of Neurological Disorders Using Machine Learning Systems Book
Author : Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam
Publisher : IGI Global
Release : 2019-06-28
ISBN : 1522585680
Language : En, Es, Fr & De

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Book Description :

While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

Convergence Mental Health

Convergence Mental Health Book
Author : Harris A. Eyre,Michael Berk,Helen Lavretsky,III Charles Reynolds
Publisher : Oxford University Press
Release : 2021-01-05
ISBN : 0197506291
Language : En, Es, Fr & De

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Book Description :

Modern mental health issues are characterized by their complex, multi-systemic nature and broad societal impact, making them poorly suited to siloed approaches of thinking and innovation. Convergence science integrates knowledge, tools, and thought strategies from various fields and is the focal point where novel insights arise. Convergence Mental Health presents a blueprint for leveraging convergence science within the context of mental health in order to improve patient outcomes and health care systems.

New Oxford Textbook of Psychiatry

New Oxford Textbook of Psychiatry Book
Author : John R. Geddes,Nancy C. Andreasen
Publisher : Oxford University Press, USA
Release : 2020-02-20
ISBN : 0198713002
Language : En, Es, Fr & De

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Book Description :

Over its two editions, The New Oxford Textbook of Psychiatry has come to be regarded as one of the most popular and trusted standard psychiatry texts among psychiatrists and trainees. Bringing together 146 chapters from the leading figures in the discipline, it presents a comprehensive account of clinical psychiatry, with reference to its scientific basis and to the patient's perspective throughout. The New Oxford Textbook of Psychiatry, Third Edition has been extensively re-structured and streamlined to keep pace with the significant developments that have taken place in the fields of clinical psychiatry and neuroscience since publication of the second edition in 2009. The new edition has been updated throughout to include the most recent versions of the two main classification systems---the DSM-5 and the ICD-11---used throughout the world for the diagnosis of mental disorders. In the years since publication of the first edition, many new and exciting discoveries have occurred in the biological sciences, which are having a major impact on how we study and practise psychiatry. In addition, psychiatry has fostered closer ties with philosophy, and these are leading to healthy discussions about how we should diagnose and treat mental illness. This new edition recognises these and other developments. Throughout, accounts of clinical practice are linked to the underlying science, and to the evidence for the efficacy of treatments. Physical and psychological treatments, including psychodynamic approaches, are covered in depth. The history of psychiatry, ethics, public health aspects, and public attitudes to psychiatry and to patients are all given due attention.