Download or read book Predictive Analytics of Psychological Disorders in Healthcare written by Mamta Mittal and published by Springer Nature. This book was released on 2022-05-20 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses an interdisciplinary field which combines two major domains: healthcare and data analytics. It presents research studies by experts helping to fight discontent, distress, anxiety and unrealized potential by using mathematical models, machine learning, artificial intelligence, etc. and take preventive measures beforehand. Psychological disorders and biological abnormalities are significantly related with the applications of cognitive illnesses which has increased significantly in contemporary years and needs rapid investigation. The research content of this book is helpful for psychological undergraduates, health workers and their trainees, therapists, medical psychologists, and nurses.
Download or read book Personalized Psychiatry written by Ives Cavalcante Passos and published by Springer. This book was released on 2019-02-12 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Personalized Psychiatry written by Flávio Kapczinski and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. .
Download or read book Mental Health Informatics written by Jessica D. Tenenbaum and published by Springer Nature. This book was released on 2021-11-18 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a detailed resource introducing the subdiscipline of mental health informatics. It systematically reviews the methods, paradigms, tools and knowledge base in both clinical and bioinformatics and across the spectrum from research to clinical care. Key foundational technologies, such as terminologies, ontologies and data exchange standards are presented and given context within the complex landscape of mental health conditions, research and care. The learning health system model is utilized to emphasize the bi-directional nature of the translational science associated with mental health processes. Descriptions of the data, technologies, paradigms and products that are generated by and used in each process and their limitations are discussed. Mental Health Informatics: Enabling a Learning Mental Healthcare System is a comprehensive introductory resource for students, educators and researchers in mental health informatics and related behavioral sciences. It is an ideal resource for use in a survey course for both pre- and post-doctoral training programs, as well as for healthcare administrators, funding entities, vendors and product developers working to make mental healthcare more evidence-based.
Download or read book Artificial Intelligence in Behavioral and Mental Health Care written by David D. Luxton and published by Academic Press. This book was released on 2015-09-10 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. Summarizes AI advances for use in mental health practice Includes advances in AI based decision-making and consultation Describes AI applications for assessment and treatment Details AI advances in robots for clinical settings Provides empirical data on clinical efficacy Explores practical issues of use in clinical settings
Download or read book Combating Women s Health Issues with Machine Learning written by D. Jude Hemanth and published by CRC Press. This book was released on 2023-10-23 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main focus of this book is the examination of women’s health issues and the role machine learning can play as a solution to these challenges. This book will illustrate advanced, innovative techniques/frameworks/concepts/machine learning methodologies, enhancing the future healthcare system. Combating Women’s Health Issues with Machine Learning: Challenges and Solutions examines the fundamental concepts and analysis of machine learning algorithms. The editors and authors of this book examine new approaches for different age-related medical issues that women face. Topics range from diagnosing diseases such as breast and ovarian cancer to using deep learning in prenatal ultrasound diagnosis. The authors also examine the best machine learning classifier for constructing the most accurate predictive model for women’s infertility risk. Among the topics discussed are gender differences in type 2 diabetes care and its management as it relates to gender using artificial intelligence. The book also discusses advanced techniques for evaluating and managing cardiovascular disease symptoms, which are more common in women but often overlooked or misdiagnosed by many healthcare providers. The book concludes by presenting future considerations and challenges in the field of women’s health using artificial intelligence. This book is intended for medical researchers, healthcare technicians, scientists, programmers and graduate-level students looking to understand better and develop applications of machine learning/deep learning in healthcare scenarios, especially concerning women’s health conditions.
Download or read book Common Mental Health Disorders written by National Collaborating Centre for Mental Health (Great Britain) and published by RCPsych Publications. This book was released on 2011 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing together treatment and referral advice from existing guidelines, this text aims to improve access to services and recognition of common mental health disorders in adults and provide advice on the principles that need to be adopted to develop appropriate referral and local care pathways.
Download or read book Big data analytics for smart healthcare applications written by Celestine Iwendi and published by Frontiers Media SA. This book was released on 2023-04-17 with total page 1365 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Patient Centric Analytics in Health Care written by Gregory J. Privitera and published by Lexington Books. This book was released on 2017-12-13 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Patient-Centric Analytics in Health Care: Driving Value in Clinical Settings and Psychological Practice, James J. Gillespie and Gregory J. Privitera introduce a framework that explores the utility of analytics for managing care that is based on six key inputs of the health care system: patients, policy makers, providers, pharmacies, pharmaceuticals, and payers. Understanding the roles of these 6 P’s and the utility of analytics to promote data-driven decision models can lead to new innovations. These improvements can enhance quality, increase access, and reduce costs, and thereby drive value for the most important stakeholders in health care: the patients. As the accessibility and volume of data continues to increase, there is a growing desire to utilize data to guide and optimize decision-making in health care environments. There is a wealth of data in health care organizations and much of it is not fully utilized. In today’s climate, these organizations are under increased regulatory and financial pressures to deliver measurable value, particularly as it relates to the quality of patient care in clinical and diagnostic settings. This book includes short contributions from practitioners, including Laurie Branch, Puneet Chahal, Patrick C. Cunningham, Star* Cunningham, Matthew Dreckmeier, Joseph P. Gaspero, Sherri Matis-Mitchell, Gail Mayeaux, Edwin K. Morris, Plamen Petrov, Steven Press, Andrew J. Privitera, Derek Walton, and Daniel Yunker.
Download or read book Microbial Metagenomics in Effluent Treatment Plant written by Maulin P. Shah and published by Elsevier. This book was released on 2024-05-24 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microbial Metagenomics in Effluent Treatment Plant introduces a metagenomic approach characterizing microbial communities?in industrial wastewater treatment, providing an overall picture of metagenomics, its application, processes, and future prospects in the field of bioremediation. It also discusses culture-dependent methods, culture-independent methods, and?enzymatic methods?used to estimate bacterial diversity to monitor temporal and spatial changes in bacterial communities. In addition, a metagenomic approach will be discussed to characterize the microbial communities in industrial wastewater treatment. Researchers, scientists, professors, and students in environmental engineering, applied microbiology, and water treatment will find Microbial Metagenomics in Effluent Treatment Plant helpful in understanding the importance and role of metagenomics in biogeochemical cycles and degradation and detoxification of environmental pollutants. Presents text rich in information and knowledge of metagenomics Introduces novel and powerful insights into the already existing bioremediation process Serves as an easy-to-understand and centralized resource of information with practical application ideas
Download or read book Computational Techniques in Neuroscience written by Kamal Malik and published by CRC Press. This book was released on 2023-11-14 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Download or read book Computational Methods in Psychiatry written by Gopi Battineni and published by Springer Nature. This book was released on 2023-11-30 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a particular area of interest in computing psychiatry with the modelling of mood and anxiety disorders. It highlights various methods for building these models. Clinical applications are prevalent due to the growth and interaction of these multiple approaches. Besides, it outlines some original predictive and computational modelling ideas for enhancing psychological treatment interventions. Computational psychiatry combines multiple levels and types of computation with different data types to improve mental illness understanding, prediction, and treatment.
Download or read book Artificial Intelligence Based System for Gaze Based Communication written by B.G.D.A. Madhusanka and published by CRC Press. This book was released on 2024-05-03 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the artificial neural network-based system for gaze-based communication. It covers the feasible and practical collaboration of human–computer interaction (HCI) in which a user can intuitively express tasks using gaze-based communication. It will target the vast applications of gaze-based communication using computer vision, image processing, and artificial intelligence. Artificial Intelligence-Based System for Gaze-Based Communication introduces a novel method to recognize the implicit intention of users by using nonverbal communication in combination with computer vision technologies. A novel HCI framework is developed to enable implicit and intuitive gaze-based intention communications. This framework allows the users to intuitively express their intention using natural gaze cues. The book also focuses on robot caregiving technology, which can understand the user’s intentions using minimal interactions with the user. The authors examine gaze-based tracking applications for the assisted living of elderly people. The book examines detailed applications of eye-gaze communication for real-life problems. It also examines the advantages that most people can handle gaze-based communications because it requires very little effort, and most of the elderly and impaired can retain visual capability. This book is ideally designed for students, researchers, academicians, and professionals interested in exploring and implementing gaze-based communication strategies and those working in the field of computer vision and image processing.
Download or read book Practical Psychiatric Epidemiology written by Jayati Das-Munshi and published by Oxford University Press. This book was released on 2020-04-30 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Epidemiology has been defined as the study of the distribution and determinants of health states or events in defined populations and its application to the control of health problems. Psychiatric epidemiology has continued to develop and apply these core principles in relation to mental health and mental disorders. This long-awaited second edition of Practical Psychiatric Epidemiology covers all of the considerable new developments in psychiatric epidemiology that have occurred since the first edition was published. It includes new content on key topics such as life course epidemiology, gene/environment interactions, bioethics, patient and public involvement in research, mixed methods research, new statistical methods, case registers, policy, and implementation. Looking to the future of this rapidly evolving scientific discipline and how it will to respond to the emerging opportunities and challenges posed by 'big data', new technologies, open science and globalisation, this new edition will continue to serve as an invaluable reference for clinicians in practice and in training. It will also be of interest to researchers in mental health and people studying or teaching psychiatric epidemiology at undergraduate or postgraduate level.
Download or read book Machine Learning and Data Analytics for Predicting Managing and Monitoring Disease written by Roy, Manikant and published by IGI Global. This book was released on 2021-06-25 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.
Download or read book Predictive Analytics in Cloud Fog and Edge Computing written by Hiren Kumar Thakkar and published by Springer Nature. This book was released on 2022-12-16 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc.
Download or read book Living with Mental Disorder written by Jacqueline Corcoran and published by Routledge. This book was released on 2016-06-10 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This evidence-based text puts a human face on mental disorders, illuminating the lived experience of people with mental health difficulties and their caregivers. Systematically reviewing the qualitative research conducted on living with a mental disorder, this text coalesces a large body of knowledge and centers on those disorders that have sufficient qualitative research to synthesize, including attention-deficit/hyperactivity disorder, autism, intellectual disabilities, mood disorders, schizophrenia and dementia. Supported by numerous quotes, the text explores the perspective of those suffering with a mental disorder and their caregivers, discovering their experience of burden, their understanding of and the meaning they give to their disorder, the strengths and coping they have used to manage, as well as their interactions with the formal treatment system and the use of medication. This book will be of immense value to students, practitioners, and academics that support, study, and treat people in mental distress and their families.