Books by Patricia B. Cerrito

Provides case studies developed by faculty and graduates of the University of Louisville's PhD program in Applied and Industrial Mathematics. The studies use non-traditional, exploratory data analysis and data mining tools to examine health outcomes, finding patterns and trends in observational data. It is ideal for the next generation of data mining practitioners.

Useful to healthcare providers, severity indices conclude which patients are most at risk for infection as well as the intensity of illness while in the hospital. This book discusses the general practice of defining a patient severity index for risk adjustments and comparison of patient outcomes to assess quality factors.

Demonstrates how concern for detail in datasets and the use of data mining techniques can extract important and meaningful knowledge from healthcare databases. Basic information on processing data with step-by-step instructions is provided, allowing readers to use their own data and follow the instructions to find meaningful results.