Download or read book Clinical Application of Machine Learning Methods in Psychiatric Disorders written by Xiaozheng Liu and published by Frontiers Media SA. This book was released on 2023-06-27 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning written by Andrea Mechelli and published by Academic Press. This book was released on 2019-11-14 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Psychiatric Neuroimaging written by Virginia Ng and published by IOS Press. This book was released on 2003 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Big Data in Psychiatry and Neurology written by Ahmed Moustafa and published by Academic Press. This book was released on 2021-06-11 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book The Cambridge Handbook of Research Methods in Clinical Psychology written by Aidan G. C. Wright and published by Cambridge University Press. This book was released on 2020-03-31 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book integrates philosophy of science, data acquisition methods, and statistical modeling techniques to present readers with a forward-thinking perspective on clinical science. It reviews modern research practices in clinical psychology that support the goals of psychological science, study designs that promote good research, and quantitative methods that can test specific scientific questions. It covers new themes in research including intensive longitudinal designs, neurobiology, developmental psychopathology, and advanced computational methods such as machine learning. Core chapters examine significant statistical topics, for example missing data, causality, meta-analysis, latent variable analysis, and dyadic data analysis. A balanced overview of observational and experimental designs is also supplied, including preclinical research and intervention science. This is a foundational resource that supports the methodological training of the current and future generations of clinical psychological scientists.
Download or read book Precision Psychiatry written by Leanne M. Williams, Ph.D. and published by American Psychiatric Pub. This book was released on 2021-10-15 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision psychiatry, as outlined in this groundbreaking book, presents a new path forward. By integrating findings from basic and clinical neuroscience, clinical practice, and population-level data, the field seeks to develop therapeutic approaches tailored for specific individuals with a specific constellation of health issues, characteristics, strengths, and symptoms.
Download or read book Mood Disorders written by Sudhakar Selvaraj and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mood disorders are the most common mental illnesses with a lifetime prevalence of up to 20% worldwide 1. Major depressive disorder (MDD) and Bipolar Disorder (BD) are significant health problems in the US and worldwide 2. In the United States alone, the lifetime prevalence of MDD is up to 17%, and that of BD about 2.1% 2 that can go up to 4% of individuals with mood episodes not meeting episodic criteria are included. Both are chronic and recurrent illnesses characterized by recurrent episodes of depression and mania and depression in MDD and BD respectively"--
Download or read book Methodological Approaches for Sleep and Vigilance Research written by Eric Murillo-Rodriguez and published by Academic Press. This book was released on 2021-10-09 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methodological Approaches for Sleep and Vigilance Research examines experimental procedures used to study the sleep-wake cycle, with topics covered by world leaders in the field. The book focuses on techniques commonly used in the sleep field, including polysomnography, electrophysiology, single- and multi-unit spiking activity recording, brain stimulation, EEG power spectra, optogenetics, telemetry, and wearable and non-wearable tracking devices. Further chapters on imaging techniques, questionnaires for sleep assessment, genome-wide association studies, artificial intelligence and big data are also featured. This discussion of significant conceptual advances into experimental procedures is suitable for anyone interested in the neurobiology of sleep. - Discusses current sleep research methodologies for experienced scientists - Focuses on techniques that allow measurement or assessment for the sleep-wake cycle - Outlines mainstream research techniques and experimental characteristics of their uses - Includes polysomnography, deep brain stimulation, and more - Reviews sleep-tracking devices, EEG and telemetry - Covers artificial intelligence and big data in analysis
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 Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Download or read book Data Classification written by Charu C. Aggarwal and published by CRC Press. This book was released on 2014-07-25 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi
Download or read book Progress in Translational Neuroimaging Integrating Pathways Systems and Phenomenology in Neurology and Psychiatry written by Drozdstoy Stoyanov and published by Frontiers Media SA. This book was released on 2020-08-21 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Learning Methods and Applications in Brain Imaging for the Diagnosis of Neurological and Psychiatric Disorders written by Hao Zhang and published by Frontiers Media SA. This book was released on 2024-10-14 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain imaging has been successfully used to generate image-based biomarkers for various neurological and psychiatric disorders, such as Alzheimer’s and related dementias, Parkinson’s disease, stroke, traumatic brain injury, brain tumors, depression, schizophrenia, etc. However, accurate brain image-based diagnosis at the individual level remains elusive, and this applies to the diagnosis of neuropathological diseases as well as clinical syndromes. In recent years, deep learning techniques, due to their ability to learn complex patterns from large amounts of data, have had remarkable success in various fields, such as computer vision and natural language processing. Applying deep learning methods to brain imaging-assisted diagnosis, while promising, is facing challenges such as insufficiently labeled data, difficulty in interpreting diagnosis results, variations in data acquisition in multi-site projects, integration of multimodal data, clinical heterogeneity, etc. The goal of this research topic is to gather cutting-edge research that showcases the application of deep learning methods in brain imaging for the diagnosis of neurological and psychiatric disorders. We encourage submissions that demonstrate novel approaches to overcome various abovementioned difficulties and achieve more accurate, reliable, generalizable, and interpretable diagnosis of neurological and psychiatric disorders in this field.
Download or read book Biomarkers in Psychiatry written by Judith Pratt and published by Springer. This book was released on 2019-01-05 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume addresses one of the Holy Grails in Psychiatry, namely the evidence for and potential to adopt ‘Biomarkers’ for prevention, diagnosis, and treatment responses in mental health conditions. It meshes together state of the art research from international renowned pre-clinical and clinical scientists to illustrate how the fields of anxiety disorders, depression, psychotic disorders, and autism spectrum disorder have advanced in recent years.
Download or read book Frontiers in Psychiatry written by Yong-Ku Kim and published by Springer Nature. This book was released on 2019-11-09 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews key recent advances and new frontiers within psychiatric research and clinical practice. These advances either represent or are enabling paradigm shifts in the discipline and are influencing how we observe, derive and test hypotheses, and intervene. Progress in information technology is allowing the collection of scattered, fragmented data and the discovery of hidden meanings from stored data, and the impacts on psychiatry are fully explored. Detailed attention is also paid to the applications of artificial intelligence, machine learning, and data science technology in psychiatry and to their role in the development of new hypotheses, which in turn promise to lead to new discoveries and treatments. Emerging research methods for precision medicine are discussed, as are a variety of novel theoretical frameworks for research, such as theoretical psychiatry, the developmental approach to the definition of psychopathology, and the theory of constructed emotion. The concluding section considers novel interventions and treatment avenues, including psychobiotics, the use of neuromodulation to augment cognitive control of emotion, and the role of the telomere-telomerase system in psychopharmacological interventions.
Download or read book Clinical Application of Psychiatric Assessment and Treatment in Psychosomatic Diseases written by Yujun Gao and published by Frontiers Media SA. This book was released on 2023-11-08 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Psychosomatic diseases are a group of diseases closely related to psychosocial factors but mainly manifested by somatic symptoms, involving respiratory, digestive, endocrine, and other systems. As a result, the lack of consensus on its diagnosis has plagued clinical treatment in internal medicine, surgery, and psychiatry for decades. In recent years, research on the pathogenesis of psychosomatic diseases has made significant progress. For example, Franz Alexander believes that unresolved subconscious conflicts are the main cause of psychosomatic disorders. The subconscious psychological conflict is caused by the changes in the functional activities of the autonomic nervous system, acting on the corresponding special organs and patients with susceptible qualities. Similarly, mental and psychological factors affect gastrointestinal sensory and motor functions through the autonomic nervous system, brain-gut axis, and neuroendocrine system. Meanwhile, gastrointestinal symptoms also affect emotions and behaviors through the brain-gut axis. In addition, the Cannon-Bard theory of emotional physiology and Pavlovian theory of higher neural activity types from quantitative research methods to study the relationship between conscious psychological factors, such as emotions, and measurable physiological and biochemical changes. In clinical work, the treatment of psychosomatic diseases has gradually shifted from emphasizing physical treatment to comprehensive treatment principles, that is, taking into account the psychological and behavioral aspects of the physical treatment of the primary disease. The main purpose of physical treatment of the primary disease is to control or relieve symptoms. To consolidate the treatment of psychosomatic diseases and reduce the recurrence of psychosomatic diseases, combining physical therapy with necessary psychotherapy would potentially obtain a more comprehensive curative effect.
Download or read book Clinical Text Mining written by Hercules Dalianis and published by Springer. This book was released on 2018-05-14 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.