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  • Format: ePub

Healthcare delivery is progressing into a format wherein analysis of a combination of disease data and patient data using predictive analytics provides additional information for physicians and healthcare providers to make more accurate detection, diagnosis, and treatment decisions. This is a unique book offering a novel course on Predictive Analytics in Healthcare. In this book, the focus in chapters is placed on reviewing and analysing the current and future applications of analytics in several health care disciplines, which can, later on, contribute to technical implementation. This book…mehr

Produktbeschreibung
Healthcare delivery is progressing into a format wherein analysis of a combination of disease data and patient data using predictive analytics provides additional information for physicians and healthcare providers to make more accurate detection, diagnosis, and treatment decisions. This is a unique book offering a novel course on Predictive Analytics in Healthcare. In this book, the focus in chapters is placed on reviewing and analysing the current and future applications of analytics in several health care disciplines, which can, later on, contribute to technical implementation. This book aims to provide comprehensive information to guide physicians, medical students, hospital administrators, biomedical engineering students, data scientists, and the industry in the proper identification of analytics applications in healthcare.

Key Features

  • Presents an overview of Predictive Analytics for physicians, medical students, biomedical engineers, and data scientists in the health care domain.
  • Identifies and presents the several existing applications of analytics in healthcare domains such as public health, women's health, telemedicine, and neurology, so that readers specializing in the particular field can have a comprehensive overview of all methodologies already in place.
  • Enables readers to identify what new applications are needed to advance the use of analytics in their field.
  • Presents case studies for the reader to understand how to us predictive analytics to bring their ideas to fruition.

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Autorenporträt
Dr Vinithasree Subbhuraam has over 15 years of experience in biomedical data science and has utilized predictive analytics for designing clinical decision support systems to detect diseases such as carotid atherosclerosis, fatty liver, diabetes, epilepsy, and cancers in the thyroid, breast, ovaries, and prostate. Her work on breast cancer has been cited in World Health Organization Handbooks on Cancer Prevention. Dr Subbhuraam is also an experienced researcher and mentor, particularly adept at designing and developing digital health solutions for highly complex technical and scientific problems that directly impact global healthcare. She has over 95 publications in high-impact factor peer-reviewed international journals, conferences, and books.