Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Author: Geeta Rani
Publisher: Medical Information Science Reference
Published: 10/16/2020
Pages: 400
Binding Type: Hardcover
Weight: 3.78lbs
Size: 11.00h x 8.50w x 1.31d
ISBN13: 9781799827429
ISBN10: 1799827429
BISAC Categories:
- Medical | Diseases
- Computers | Machine Theory
- Computers | Data Science | Data Visualization

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