Big Data in Psychiatry and Neurology: An Overview

Big Data in Psychiatry and Neurology, authored by Ahmed Moustafa, provides a comprehensive overview of the advancements in the field of big data in Psychiatry and Medicine. This book focuses on the applications of big data methods to various disorders, including aging disorders such as Alzheimer’s disease and Parkinson’s disease, mood disorders like major depressive disorder, and drug addiction.

Researchers, students, and clinicians will find this book particularly useful as it guides them on how to collect big datasets from different patient populations and apply various algorithms and machine learning methods to analyze these datasets. This analysis can lead to individualized treatment plans for psychiatric and neurological patients.

Big Data Analytics in Psychiatric Research

Big data analytics is increasingly being used in psychiatric research, providing predictive models for both clinical practice and public health systems. Unlike traditional statistical methods that offer average group-level results, big data analytics enables predictions and stratification of clinical outcomes at an individual subject level.

Longitudinal Big Data and Risk Factors

The book discusses longitudinal big data and the risk factors associated with the development of psychiatric disorders. It delves into the methods of using big data to treat psychiatric and neurological disorders, highlighting the role of machine learning in the analysis of big data.

Methods of Gathering Big Data in Medicine

Big Data in Psychiatry and Neurology also describes the various methods of gathering big data in medicine. It reviews how to apply big data to genetics, providing insights into the genetic factors that contribute to psychiatric and neurological disorders.

This book serves as a valuable resource for those interested in the intersection of big data and psychiatry, offering practical guidance on leveraging big data to improve patient outcomes and advance research in the field.