Preface

ABSTRACT

Data science has improved healthcare as new data sources and analytic techniques have become available. Data science applications are valuable technologies, which could powerfully improve health care service delivery, especially in mental illness. COVID-19's undesired psychological health repercussions, such as depression symptoms, have been widely anticipated. COVID-19 has several physical health risk factors;however, it is unknown if there are any psychological risk factors. Data science enables statistical cooperation, data analytic technique development, and data administration for psychiatric and mental health research. Although data science is not commonly employed in the mental health profession, there is hopeful evidence that it can substantially affect it. Researchers may use data science to evaluate mental diseases' consequences in the US and worldwide. When the consequences are measured and backed up by statistics, it makes a stronger argument for much-needed provisions. When the consequences are defined and validated by evidence, it provides a robust discussion for allocating critical resources to accessible psychological health diagnosis and care. Diagnostic reports, pharmaceutical sales, physicians' observations, and diagnostic testing are all examples of data. Data from health applications and monitoring tools can be used to gain valuable insights and, ultimately, break the stigma of psychiatric conditions in enhancing health care. © 2022 Nova Science Publishers, Inc. All rights reserved.