Predictive Analytics using MATLAB(R) for Biomedical Applications
Published on 26. September 2024
Book
Paperback/Softback
480 pages
978-0-443-29888-2 (ISBN)
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.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
College/higher education
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 234 mm
Width: 188 mm
Thickness: 25 mm
Weight
916 gr
ISBN-13
978-0-443-29888-2 (9780443298882)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
E-Book
10/2024
Academic Press
€167.99
Available for download
Person
Professor Ashok Kumar is Principal at
Thiagarajar College of Engineering, Madurai, India.
His current research focuses on integration of renewable energy systems in the smart grid, biomedical applications, and wearable electronics. He has three years of industrial experience and 24 years of academic and research experience. He is also the author of several books and technical papers in national and international journals.
Thiagarajar College of Engineering, Madurai, India.
His current research focuses on integration of renewable energy systems in the smart grid, biomedical applications, and wearable electronics. He has three years of industrial experience and 24 years of academic and research experience. He is also the author of several books and technical papers in national and international journals.
Content
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