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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
Researchers and students in Psychiatry and Neurology designing protocols; Clinicians involved in clinical trials
1. The need for big data in neurology and psychiatry
Prof. Russ Altman, MD, PhD, Bioengineering, Genetics and Medicine, Stanford University
2. Methods of gathering big data in medicine
A/prof. Ahmed Moustafa, Western Sydney University
3. Longitudinal big data and risk factors of the development of psychiatric disorders
Prof. Peter Schofield, King's College London
4. The analysis of big data: the role of machine learning
Dr. Ron Alfa, MD, PhD, Senior Vice President, Translational Discovery at Recursion, a technology-enabled drug discovery
5. A big data approach to understanding old-age disorders
Dr. Suji Ham, Convergence Research Center for Diagnosis, Treatment and Care System of Dementia, Korea Institute of Science and Technology (KIST), Seoul, South Korea
6. Using big data methods to treat mood disorders
Dr. Thierno Diallo, Lecturer of biostatistics, Western Sydney University
7. Big data and managing different drug addictions
Sunny Jung Kim
8. How can big data aid in the treatment of neurological disorders
Dr. Siuly Siuly, Centre for Applied Informatics, College of Engineering and ScienceVictoria UniversityMelbourneAustralia
9. Examples of success of big data in medicine
Prof. Hany Alashwal, United Arab Emirates University, Al Ain, UAE
10. The interdisciplinary nature of big data: the marriage of medicine and analytics
Prof. Kirsten Bibbins-Domingo, Chair, Department of Epidemiology and Biostatistics University of California, San Francisco
11. Applying big data to genetics
Prof. Tiffany F Boughtwood, Murdoch Children's Research Institute, Melbourne
12. Big Data and Precision medicine
- No. of pages:
- © Academic Press 2021
- 1st May 2021
- Academic Press
- Paperback ISBN:
Dr. Ahmed A. Moustafa is an associate professor of cognitive and behavioral neuroscience at the Marcs Institute for Brain, Behaviour, Development and School of Psychology, Western Sydney University, Sydney, Australia. Before joining Western Sydney University as a lab director, Dr. Moustafa spent 11 years in the United States studying psychology and neuroscience. His research focuses on computational and neuropsychological studies of addiction, schizophrenia, Alzheimer’s disease, PTSD, and depression. Dr. Moustafa’s works have been cited nearly 9000 times. He has published four books and more than 200 papers in high-ranking journals including Science, PNAS, Journal of Neuroscience, Brain, Neuroscience and Biobehavioral Reviews, Nature (Parkinson’s disease), and Neuron.
Marcs Institute for Brain, Behaviour, Development and School of Psychology, Western Sydney University, Sydney, Australia
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