Predictive Analytics of Psychological Disorders in Healthcare: Data Analytics on Psychological Disorders

This book discusses an interdisciplinary field that combines healthcare and data analytics to fight discontent, distress, anxiety, and unrealized potential by using mathematical models, machine learning, artificial intelligence, and other techniques. It is helpful for psychological undergraduates, health workers, therapists, medical psychologists, and nurses.

Format: Paperback / softback
Length: 303 pages
Publication date: 22 May 2022
Publisher: Springer Verlag, Singapore

This captivating book delves into an interdisciplinary realm that seamlessly blends two pivotal domains: healthcare and data analytics. It showcases a wealth of research studies conducted by esteemed experts, aimed at alleviating discontent, distress, anxiety, and unrealized potential through the utilization of mathematical models, machine learning, artificial intelligence, and other cutting-edge technologies. By employing these tools, individuals can take proactive measures to prevent psychological disorders and biological abnormalities from escalating, a pressing concern that has grown significantly in modern times. The research content within this book is invaluable for psychological undergraduates, healthcare professionals, their trainees, therapists, medical psychologists, and nurses alike.

The field of healthcare and data analytics is a rapidly evolving domain that combines the expertise of healthcare professionals with the power of data analysis to improve patient outcomes and enhance healthcare systems. This interdisciplinary approach involves the use of advanced technologies such as artificial intelligence, machine learning, and big data analytics to analyze healthcare data and extract valuable insights.

One of the key areas of focus in healthcare and data analytics is the development of predictive models that can help healthcare providers identify patients who are at risk of developing certain diseases or conditions. These models can be based on a wide range of data sources, including patient demographics, medical history, laboratory results, and clinical outcomes. By using these models, healthcare providers can intervene early and provide personalized care to patients, reducing the risk of complications and improving overall health outcomes.

Another important area of healthcare and data analytics is the use of data visualization to communicate complex information to healthcare professionals and patients. Data visualization techniques such as charts, graphs, and infographics can help healthcare providers understand patient data more easily and make informed decisions about patient care. This can be particularly useful in areas such as medicine, where there is a large amount of data to analyze and interpret.

In addition to these areas, healthcare and data analytics also involves the use of natural language processing and machine learning to analyze patient data and generate meaningful insights. Natural language processing allows healthcare providers to understand and interpret patient queries and complaints more accurately, while machine learning algorithms can help identify patterns and trends in patient data that may not be apparent to human analysts.

Overall, healthcare and data analytics is a rapidly evolving field that has the potential to transform the way healthcare is delivered and improve patient outcomes. By leveraging advanced technologies and analytical techniques, healthcare professionals can gain a deeper understanding of patient data and make more informed decisions about patient care.

Weight: 492g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811917233
Edition number: 1st ed. 2022