Product details:
| ISBN13: | 9780443298882 |
| ISBN10: | 0443298882 |
| Binding: | Paperback |
| No. of pages: | 480 pages |
| Size: | 234x190 mm |
| Weight: | 450 g |
| Language: | English |
| 700 |
Category:
Predictive Analytics using MATLAB(R) for Biomedical Applications
Series:
Clinical and Medical Innovation;
Publisher: Academic Press
Date of Publication: 1 October 2024
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Publisher's listprice:
EUR 167.99
EUR 167.99
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Long description:
Predictive Analytics using MATLAB(R) for Biomedical Applications is a comprehensive and practical guide for biomedical engineers, data scientists, and researchers on how to use predictive analytics techniques in MATLAB(R) for solving real-world biomedical problems. The book offers a technical overview of various predictive analytics methods and covers the utilization of MATLAB(R) for implementing these techniques. It includes several case studies that demonstrate how predictive analytics can be applied to real-world biomedical problems, such as predicting disease progression, analyzing medical imaging data, and optimizing treatment outcomes.
With a plethora of examples and exercises, this book is the ultimate tool for reinforcing one’s knowledge and skills.
With a plethora of examples and exercises, this book is the ultimate tool for reinforcing one’s knowledge and skills.
Table of Contents:
1. Introduction to the art of predictive analysis
2. Prognostic insights: predictive analytics in nephrological diseases
3. Harnessing predictive analytics for cardiovascular diseases
4. Predictive analytics in breast cancer prognosis
5. Predicting Parkinson’s: analyzing patterns with data and analytics
6. Predictive analytics for diabetes mellitus: illuminating glucose horizons
7. From data to diagnosis: predictive analytics in liver ailments
8. Predictive analytics in Alzheimer’s disease: pioneering memory projection
9. Prostate cancer prognostication: insights from predictive analytics
10. Leveraging predictive analytics for asthma management
11. Predictive analytics for brain tumor detection and prognosis
12. A comprehensive overview of predictive analytics in biomedical applications
2. Prognostic insights: predictive analytics in nephrological diseases
3. Harnessing predictive analytics for cardiovascular diseases
4. Predictive analytics in breast cancer prognosis
5. Predicting Parkinson’s: analyzing patterns with data and analytics
6. Predictive analytics for diabetes mellitus: illuminating glucose horizons
7. From data to diagnosis: predictive analytics in liver ailments
8. Predictive analytics in Alzheimer’s disease: pioneering memory projection
9. Prostate cancer prognostication: insights from predictive analytics
10. Leveraging predictive analytics for asthma management
11. Predictive analytics for brain tumor detection and prognosis
12. A comprehensive overview of predictive analytics in biomedical applications