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Leveraging Longitudinal Data For Predictive Modeling In Clinical And Mental Health Settings
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Book Synopsis Leveraging Longitudinal Data for Predictive Modeling in Clinical and Mental Health Settings by : Argus J. Athanas-Crannell
Download or read book Leveraging Longitudinal Data for Predictive Modeling in Clinical and Mental Health Settings written by Argus J. Athanas-Crannell and published by . This book was released on 2020 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are at a pivotal point in healthcare informatics where our technical abilities and computational methods are often beyond our abilities to translate and implement them in practical and applied settings. For example, researchers are working on unraveling the intricacies of the human genome to help individuals with their healthcare needs, but often lack the ability to easily share genetic data and medical records between clinics or healthcare providers due to logistical, legal, and interoperability issues. Using more sophisticated healthcare data on individuals derived from other data-intensive assays, such imaging or digital devices, to guide their care is likely to create even more practical issues. This will especially be the case as the community pushes towards personalized medicine and an ability to track an individual's health over time through the use of these data-intensive assays. In my thesis research, I consider the application of statistical methods to large-scale longitudinal health data. I focus on not only the detection of novel relationships between longitudinal data points, but also on developing strategies for making more personalized health predictions and recommendations. I focus on three broad settings: one involving an analysis of genetic factors associated with progressive visual field loss in patients with primary open angle glaucoma using a large clinical data set, and two that consider individual mental health and mood data obtained from the prolonged use of a digital therapeutic (i.e., smartphone app) designed to provide meditations to individual users to reduce stress, anxiety, and depression. I also discuss and explore the implementation of systems designed to learn or adapt from past data in order to improve predictive models going forward using the glaucoma and healthcare app data.
Book Synopsis Leveraging Longitudinal Data in Developing Countries by : National Research Council
Download or read book Leveraging Longitudinal Data in Developing Countries written by National Research Council and published by National Academies Press. This book was released on 2002-06-13 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal data collection and analysis are critical to social, demographic, and health research, policy, and practice. They are regularly used to address questions of demographic and health trends, policy and program evaluation, and causality. Panel studies, cohort studies, and longitudinal community studies have proved particularly important in developing countries that lack vital registration systems and comprehensive sources of information on the demographic and health situation of their populations. Research using data from such studies has led to scientific advances and improvements in the well-being of individuals in developing countries. Yet questions remain about the usefulness of these studies relative to their expense (and relative to cross-sectional surveys) and about the appropriate choice of alternative longitudinal strategies in different contexts. For these reasons, the Committee on Population convened a workshop to examine the comparative strengths and weaknesses of various longitudinal approaches in addressing demographic and health questions in developing countries and to consider ways to strengthen longitudinal data collection and analysis. This report summarizes the discussion and opinions voiced at that workshop.
Book Synopsis Predictive Modeling for High Dimensional Longitudinal Data by : Junjie Liang
Download or read book Predictive Modeling for High Dimensional Longitudinal Data written by Junjie Liang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal studies, which involve repeated observations, taken at irregularly spaced time points, for a set of individuals over time, are ubiquitous in many applications. Predictive models for longitudinal data generally need to take into account the data correlation, i.e., correlation among repeated observations of the individual and/or correlation among groups of individuals. Ignoring either part of the correlation can lead to misleading statistical inferences. It can be non-trivial to choose a suitable correlation structure that reflects the correlations present in the data. The relationships between the variables and outcomes of interest can be highly complex and non-linear. Furthermore, modern applications often call for longitudinal methods that scale gracefully with increasing number of variables and millions of data points. The target for this dissertation is to address the challenges in longitudinal data analysis using machine learning and representation learning approaches. Specifically, our work is dedicated to redesign the state-of-the-art longitudinal models to fit in the large-scale, high-dimensional longitudinal settings. We focus on improving the mixed effects models and non-parametric models by answering the following research questions: (i) How can we design mixed effects models to handle longitudinal data with thousands of variables and automate the selection between fixed and random effects? (ii) How can we design non-parametric models to handle longitudinal data with time-varying and time-invariant effects and automate the discovery of complex correlation? (iii) How can we design non-parametric models to handle longitudinal data with outcomes that could show state transitions, abrupt discontinuities and complex correlation? Against this background, this dissertation investigates two lines of approaches, Factorization Machines and Gaussian Process. We tackle both the theoretical and practical challenges in adapting these approaches to longitudinal settings. For each proposed model, we explore provably efficient algorithm to improve its applicability over high-dimensional data.
Book Synopsis Big Data in Psychiatry and Neurology by : Ahmed Moustafa
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
Book Synopsis Pipelines for Deep Contextual Patient-level Clinical Outcome Prediction by : Rohan S. Kodialam
Download or read book Pipelines for Deep Contextual Patient-level Clinical Outcome Prediction written by Rohan S. Kodialam and published by . This book was released on 2020 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal health data provides a uniquely detailed view into the evolution of patient health over time. We develop pipelines to efficiently work with this kind of data in its rawest form, enabling the development of new state-of-the-art end-to-end machine learning approaches. While healthcare providers are increasingly using learned methods to predict and understand long-term patient outcomes in order to make meaningful interventions, deep learning models often struggle to match performance of shallow linear models in predicting these outcomes, making it difficult to leverage such techniques in practice. Motivated by the task of clinical prediction from longitudinal health data, we present a new technique called reverse distillation which pre-trains deep models by using high-performing linear models for initialization. We make use of the longitudinal structure of our dataset to develop Self Attention with Reverse Distillation, or SARD, an architecture that utilizes a combination of contextual embedding, temporal embedding and self-attention mechanisms and most critically is trained via reverse distillation. SARD outperforms state-of-the-art methods on multiple clinical prediction outcomes, with ablation studies revealing that reverse distillation is the primary driver of these improvements.
Book Synopsis Artificial Intelligence and Mental Health Care by : Jorge Piano Simoes
Download or read book Artificial Intelligence and Mental Health Care written by Jorge Piano Simoes and published by Frontiers Media SA. This book was released on 2024-08-09 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: New developments in machine learning (ML) and artificial intelligence (AI) hold great promise to revolutionize mental health care. In this context, ML and AI have been deployed for several different goals, including 1) the early detection of mental disorders, 2) the optimization of personalized treatments based on the individual characteristics of patients, 3) the better characterization of disorders detrimental to mental well-being and quality of life, as well as a better description of projected trajectories over time, and 4) the development of new treatments for mental health care. Despite their great potential to transform mental health care and occasional breakthroughs, ML and AI have not yet fully achieved these goals. This research topic aims to bridge the gap between the potential uses of ML and AI and their practical application in standard mental health care. More specifically, we welcome original research submissions applying ML and AI to promote public health by reducing the burden of chronic disorders with detrimental effects on well-being (e.g., psychopathological distress), and improving quality of life. We also welcome submissions applying ML and AI in heterogeneous datasets (e.g., subjective scales and questionnaires, biomarkers, (neuro)psychological assessments, etc.) from Big Data sources (e.g., large datasets of clinical populations, electronic health records from nationally representative cohorts, and/or biobanks, studies using experiencing sampling methods, etc.) to gain mechanistic insight on how different chronic conditions associated with psychopathological distress can affect patient well-being and quality of life. Finally, we also welcome opinion papers and reviews on how to develop AI applications in mental health care responsibly, while integrating biopsychosocial aspects of patients to promote better mental health care.
Book Synopsis Personalized Psychiatry by : Bernhard Baune
Download or read book Personalized Psychiatry written by Bernhard Baune and published by Academic Press. This book was released on 2019-10-16 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Personalized Psychiatry presents the first book to explore this novel field of biological psychiatry that covers both basic science research and its translational applications. The book conceptualizes personalized psychiatry and provides state-of-the-art knowledge on biological and neuroscience methodologies, all while integrating clinical phenomenology relevant to personalized psychiatry and discussing important principles and potential models. It is essential reading for advanced students and neuroscience and psychiatry researchers who are investigating the prevention and treatment of mental disorders. Combines neurobiology with basic science methodologies in genomics, epigenomics and transcriptomics Demonstrates how the statistical modeling of interacting biological and clinical information could transform the future of psychiatry Addresses fundamental questions and requirements for personalized psychiatry from a basic research and translational perspective
Book Synopsis Precision Medicine and Artificial Intelligence by : Michael Mahler
Download or read book Precision Medicine and Artificial Intelligence written by Michael Mahler and published by Academic Press. This book was released on 2021-03-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions Provides background, milestone and examples of precision medicine Outlines the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using AI Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309493439 Total Pages :195 pages Book Rating :4.3/5 (94 download)
Book Synopsis Integrating Social Care into the Delivery of Health Care by : National Academies of Sciences, Engineering, and Medicine
Download or read book Integrating Social Care into the Delivery of Health Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-01-30 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health was released in September 2019, before the World Health Organization declared COVID-19 a global pandemic in March 2020. Improving social conditions remains critical to improving health outcomes, and integrating social care into health care delivery is more relevant than ever in the context of the pandemic and increased strains placed on the U.S. health care system. The report and its related products ultimately aim to help improve health and health equity, during COVID-19 and beyond. The consistent and compelling evidence on how social determinants shape health has led to a growing recognition throughout the health care sector that improving health and health equity is likely to depend â€" at least in part â€" on mitigating adverse social determinants. This recognition has been bolstered by a shift in the health care sector towards value-based payment, which incentivizes improved health outcomes for persons and populations rather than service delivery alone. The combined result of these changes has been a growing emphasis on health care systems addressing patients' social risk factors and social needs with the aim of improving health outcomes. This may involve health care systems linking individual patients with government and community social services, but important questions need to be answered about when and how health care systems should integrate social care into their practices and what kinds of infrastructure are required to facilitate such activities. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health examines the potential for integrating services addressing social needs and the social determinants of health into the delivery of health care to achieve better health outcomes. This report assesses approaches to social care integration currently being taken by health care providers and systems, and new or emerging approaches and opportunities; current roles in such integration by different disciplines and organizations, and new or emerging roles and types of providers; and current and emerging efforts to design health care systems to improve the nation's health and reduce health inequities.
Book Synopsis Leveraging Data Science for Global Health by : Leo Anthony Celi
Download or read book Leveraging Data Science for Global Health written by Leo Anthony Celi and published by Springer Nature. This book was released on 2020-07-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Author :Agency for Healthcare Research and Quality/AHRQ Publisher :Government Printing Office ISBN 13 :1587634333 Total Pages :385 pages Book Rating :4.5/5 (876 download)
Book Synopsis Registries for Evaluating Patient Outcomes by : Agency for Healthcare Research and Quality/AHRQ
Download or read book Registries for Evaluating Patient Outcomes written by Agency for Healthcare Research and Quality/AHRQ and published by Government Printing Office. This book was released on 2014-04-01 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
Book Synopsis Kernel Methods in Computational Biology by : Bernhard Schölkopf
Download or read book Kernel Methods in Computational Biology written by Bernhard Schölkopf and published by MIT Press. This book was released on 2004 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed overview of current research in kernel methods and their application to computational biology.
Book Synopsis Applied Longitudinal Data Analysis by : Judith D. Singer
Download or read book Applied Longitudinal Data Analysis written by Judith D. Singer and published by Oxford University Press. This book was released on 2003-03-27 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives.
Book Synopsis Implementation of Social and Emotional Learning Interventions in Applied Settings: Approaches to Definition, Measurement, and Analysis by : Stephanie M. Jones
Download or read book Implementation of Social and Emotional Learning Interventions in Applied Settings: Approaches to Definition, Measurement, and Analysis written by Stephanie M. Jones and published by Frontiers Media SA. This book was released on 2023-10-06 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309493382 Total Pages :621 pages Book Rating :4.3/5 (94 download)
Book Synopsis Vibrant and Healthy Kids by : National Academies of Sciences, Engineering, and Medicine
Download or read book Vibrant and Healthy Kids written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-12-27 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: Children are the foundation of the United States, and supporting them is a key component of building a successful future. However, millions of children face health inequities that compromise their development, well-being, and long-term outcomes, despite substantial scientific evidence about how those adversities contribute to poor health. Advancements in neurobiological and socio-behavioral science show that critical biological systems develop in the prenatal through early childhood periods, and neurobiological development is extremely responsive to environmental influences during these stages. Consequently, social, economic, cultural, and environmental factors significantly affect a child's health ecosystem and ability to thrive throughout adulthood. Vibrant and Healthy Kids: Aligning Science, Practice, and Policy to Advance Health Equity builds upon and updates research from Communities in Action: Pathways to Health Equity (2017) and From Neurons to Neighborhoods: The Science of Early Childhood Development (2000). This report provides a brief overview of stressors that affect childhood development and health, a framework for applying current brain and development science to the real world, a roadmap for implementing tailored interventions, and recommendations about improving systems to better align with our understanding of the significant impact of health equity.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309495474 Total Pages :335 pages Book Rating :4.3/5 (94 download)
Book Synopsis Taking Action Against Clinician Burnout by : National Academies of Sciences, Engineering, and Medicine
Download or read book Taking Action Against Clinician Burnout written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2020-01-02 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Patient-centered, high-quality health care relies on the well-being, health, and safety of health care clinicians. However, alarmingly high rates of clinician burnout in the United States are detrimental to the quality of care being provided, harmful to individuals in the workforce, and costly. It is important to take a systemic approach to address burnout that focuses on the structure, organization, and culture of health care. Taking Action Against Clinician Burnout: A Systems Approach to Professional Well-Being builds upon two groundbreaking reports from the past twenty years, To Err Is Human: Building a Safer Health System and Crossing the Quality Chasm: A New Health System for the 21st Century, which both called attention to the issues around patient safety and quality of care. This report explores the extent, consequences, and contributing factors of clinician burnout and provides a framework for a systems approach to clinician burnout and professional well-being, a research agenda to advance clinician well-being, and recommendations for the field.
Book Synopsis Latent Class and Latent Transition Analysis by : Linda M. Collins
Download or read book Latent Class and Latent Transition Analysis written by Linda M. Collins and published by John Wiley & Sons. This book was released on 2013-05-20 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern, comprehensive treatment of latent class and latent transition analysis for categorical data On a daily basis, researchers in the social, behavioral, and health sciences collect information and fit statistical models to the gathered empirical data with the goal of making significant advances in these fields. In many cases, it can be useful to identify latent, or unobserved, subgroups in a population, where individuals' subgroup membership is inferred from their responses on a set of observed variables. Latent Class and Latent Transition Analysis provides a comprehensive and unified introduction to this topic through one-of-a-kind, step-by-step presentations and coverage of theoretical, technical, and practical issues in categorical latent variable modeling for both cross-sectional and longitudinal data. The book begins with an introduction to latent class and latent transition analysis for categorical data. Subsequent chapters delve into more in-depth material, featuring: A complete treatment of longitudinal latent class models Focused coverage of the conceptual underpinnings of interpretation and evaluationof a latent class solution Use of parameter restrictions and detection of identification problems Advanced topics such as multi-group analysis and the modeling and interpretation of interactions between covariates The authors present the topic in a style that is accessible yet rigorous. Each method is presented with both a theoretical background and the practical information that is useful for any data analyst. Empirical examples showcase the real-world applications of the discussed concepts and models, and each chapter concludes with a "Points to Remember" section that contains a brief summary of key ideas. All of the analyses in the book are performed using Proc LCA and Proc LTA, the authors' own software packages that can be run within the SAS® environment. A related Web site houses information on these freely available programs and the book's data sets, encouraging readers to reproduce the analyses and also try their own variations. Latent Class and Latent Transition Analysis is an excellent book for courses on categorical data analysis and latent variable models at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners in the social, behavioral, and health sciences who conduct latent class and latent transition analysis in their everyday work.
