Big Data in Psychiatry and Neurology

Erscheinungsjahr 2021
ISBN: 978-0-12-822884-5
Verlag: William Andrew Publishing

Buch, Englisch, 384 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 570 g

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.

Autoren/Hrsg.

Moustafa, Ahmed

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Neurobiologie, Verhaltensbiologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Psychiatrie, Sozialpsychiatrie, Suchttherapie

Inhaltsverzeichnis

1. Best practices for supervised machine learning when examining biomarkers in clinical populations Benjamin G. Schultz, Zaher Joukhadar, Usha Nattala, Maria del Mar Quiroga, Francesca Bolk, and Adam P. Vogel

2. Big data in personalized healthcare Lidong Wang and Cheryl Alexander

3. Longitudinal data analysis: The multiple indicators growth curve model approach Thierno M.O. Diallo and Ahmed A. Moustafa

4. Challenges and solutions for big data in personalized healthcare Tim Hulsen

5. Data linkages in epidemiology Sinead Moylett

6. Neutrosophic rule-based classification system and its medical applications Sameh H. Basha, Areeg Abdalla, and Aboul Ella Hassanien

7. From complex to neural networks Nicola Amoroso and Loredana Bellantuono

8. The use of Big Data in psychiatry-The role of administrative databases Manuel Goncalves-Pinho and Alberto Freitas

9. Predicting the emergence of novel psychoactive substances with big data Robert Todd Perdue and James Hawdon

10. Hippocampus segmentation in MR images: Multiatlas methods and deep learning methods Hancan Zhu, Shuai Wang, Liangqiong Qu, and Dinggang Shen

11. A scalable medication intake monitoring system Diane Myung-Kyung Woodbridge and Kevin Bengtson Wong

12. Evaluating cascade prediction via different embedding techniques for disease mitigation Abhinav Choudhury, Shubham Shakya, Shruti Kaushik, and Varun Dutt

13. A two-stage classification framework for epileptic seizure prediction using EEG wavelet-based features Sahar Elgohary, Mahmoud I. Khalil, and Seif Eldawlatly

14. Visual neuroscience in the age of big data and artificial intelligence Kohitij Kar

15. Application of big data and artificial intelligence approaches in diagnosis and treatment of neuropsychiatric diseases Qiurong Song, Tianhui Huang, Xinyue Wang, Jingxiao Niu, Wang Zhao, Haiqing Xu, and Long Lu

16. Leveraging big data to augment evidence-informed precise public health response G.V. Asokan and Mohammed Yousif Abbas Mohammed

17. How big data analytics is changing the face of precision medicine in women's health Maryam Panahiazar, Maryam Karimzadehgan, Roohallah Alizadehsani, Dexter Hadley, and Ramin E. Beygui

Über Autor(innen)

Moustafa, Ahmed
Dr. Ahmed Moustafa is a Professor of Psychology and Computational Modeling at School of Psychology, Bond University, Gold Coast, Queensland, Australia. Prior to moving to Bond University, Ahmed was an associate professor in Psychology and Neuroscience at Marcs Institute for Brain, Behavior, and Development & School of Psychology, Western Sydney University. Ahmed is trained in computer science, psychology, neuroscience, and cognitive science. His early training took place at Cairo University in mathematics and computer science. Before joining Western Sydney University as a lab director, Ahmed spent 11 years in America working on several psychology and neuroscience projects. Ahmed conducts research on computational and neuropsychological studies of addiction, schizophrenia, Parkinson's disease, PTSD, depression, Alzheimer's disease. He has published over 240 papers in high-ranking journals including Science, PNAS, Journal of Neuroscience, Brain, Neuroscience and Biobehavioral Reviews, Nature (Parkinson's disease), Neuron, among others. Ahmed has obtained grant funding from Australia, USA, Qatar, UAE, Turkey, and other countries. Ahmed has recently published ten books: (1) Computational models of brain and behavior; (2) Social Cognition in Psychosis, (3) computational Neuroscience Models of the Basal Ganglia, (4) Cognitive, Clinical, and Neural Aspects of Drug Addiction; (5) The Nature of Depression: An updated review; (6) Big data in psychiatry and neurology; (7) Alzheimer's Disease: Understanding Biomarkers, Big Data, and Therapy. Elsevier; (8) Cognitive and Behavioral Dysfunction in Schizophrenia; (9) Female Pioneers from Ancient Egypt and the Middle East; and (10) Mental health effects of COVID-19. In the last 10 years, Ahmed has published collaboratively with 71 colleagues, has more than 510 co-authors, from 35 institutions in 14 countries. Ahmed is now Editor-in-Chief of Discover Psychology, a new journal by Springer Nature.