Predictive Analytics using MATLAB(R) for Biomedical Applications

Häftad, Engelska, 2024

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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.

Covers various predictive analytics methods, including regression analysis, time series analysis, and machine learning algorithms, providing readers with a comprehensive understanding of the field
Provides a hands-on approach to learning predictive analytics, with a focus on practical applications in biomedical engineering
Includes several case studies that demonstrate the practical application of predictive analytics in real-world biomedical problems, such as disease progression prediction, medical imaging analysis, and treatment optimization

Produktinformation

Utgivningsdatum2024-09-26
Mått191 x 235 x 25 mm
Vikt990 g
FormatHäftad
SpråkEngelska
Antal sidor480
FörlagElsevier Science
ISBN9780443298882

Tillhör följande kategorier

Biokemisk teknik inom Naturvetenskap och teknik
Biomedicinsk teknik inom Medicin
Affärsapplikationer inom Data och it

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.

1. Introduction to the art of predictive analysis2. Prognostic insights: predictive analytics in nephrological diseases3. Harnessing predictive analytics for cardiovascular diseases4. Predictive analytics in breast cancer prognosis5. Predicting Parkinson’s: analyzing patterns with data and analytics6. Predictive analytics for diabetes mellitus: illuminating glucose horizons7. From data to diagnosis: predictive analytics in liver ailments8. Predictive analytics in Alzheimer’s disease: pioneering memory projection9. Prostate cancer prognostication: insights from predictive analytics10. Leveraging predictive analytics for asthma management11. Predictive analytics for brain tumor detection and prognosis12. A comprehensive overview of predictive analytics in biomedical applications