Predictive Analytics using MATLAB(R) for Biomedical Applications (Clinical and Medical Innovation) - Softcover

Kumar

 
9780443298882: Predictive Analytics using MATLAB(R) for Biomedical Applications (Clinical and Medical Innovation)

Inhaltsangabe

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.

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Über die Autorin bzw. den Autor

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.

Von der hinteren Coverseite

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.

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