Machine Learning Biomedical Engineers (12 results)

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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

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Condition: New. Vijay Jeyakumar is an Associate Professor in the Department of Biomedical Engineering at SSN College of Engineering, Chennai, with more than 18 years of academic and research experience. He completed his Ph.D. in Medical Informatics (2015) and M.E.

Buch. Condition: Neu. Neuware - This book combines machine learning (ML) and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customised medicine, medical imaging analysis, disease detection, and health monitoring. It contains case studies and examples that show how various ML algorithms are used on biomedical data sets. The ethical issues and difficulties unique to using ML in biomedical settings, such as data privacy, algorithm bias, and regulatory compliance are also covered. - Provides a broad introduction to ML in biomedicine and biomedical engineering - Discusses ethical considerations and explainability pertinent to ML in bioengineering - Explores step-by-step tutorials, coding examples, and real-world case studies - Reviews feature selection, training and evaluating models, preprocessing data, and validation techniques tailored to biomedical data - Includes MATLAB and Python coding programs This book is aimed at graduate students and researchers in bioengineering and ML. …

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is written for a broad audience: orthopedic and dental surgeons evaluating new diagnostic tools, biomedical researchers designing the next generation of smart implants, data scientists entering the healthcare domain, and students seeking a structured overview of this fast-moving interdisciplinary field. No single background is assumed; technical concepts are introduced from first principles, and clinical context is provided throughout.…

Taschenbuch. Condition: Neu. Machine Learning in Implant Success Detection | A Comprehensive Guide for Clinicians, Researchers, and Biomedical Engineers | Rohit Nandan (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630109238 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …

Hardcover. Condition: new. Hardcover. This book combines machine learning (ML) and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customised medicine, medical imaging analysis, disease detection, and health monitoring. It contains case studies and examples that show how various ML algorithms are used on biomedical data sets. The ethical issues and difficulties unique to using ML in biomedical settings, such as data privacy, algorithm bias, and regulatory compliance are also covered.Provides a broad introduction to ML in biomedicine and biomedical engineeringDiscusses ethical considerations and explainability pertinent to ML in bioengineeringExplores step-by-step tutorials, coding examples, and real-world case studiesReviews feature selection, training and evaluating models, preprocessing data, and validation techniques tailored to biomedical dataIncludes MATLAB and Python coding programsThis book is aimed at graduate students and researchers in bioengineering and ML This book combines machine learning and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customized medicine, medical imaging analysis, disease detection, and health monitoring. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condition: new. Hardcover. This book combines machine learning (ML) and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customised medicine, medical imaging analysis, disease detection, and health monitoring. It contains case studies and examples that show how various ML algorithms are used on biomedical data sets. The ethical issues and difficulties unique to using ML in biomedical settings, such as data privacy, algorithm bias, and regulatory compliance are also covered.Provides a broad introduction to ML in biomedicine and biomedical engineeringDiscusses ethical considerations and explainability pertinent to ML in bioengineeringExplores step-by-step tutorials, coding examples, and real-world case studiesReviews feature selection, training and evaluating models, preprocessing data, and validation techniques tailored to biomedical dataIncludes MATLAB and Python coding programsThis book is aimed at graduate students and researchers in bioengineering and ML This book combines machine learning and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customized medicine, medical imaging analysis, disease detection, and health monitoring. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Condition: new. Hardcover. This book combines machine learning (ML) and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customised medicine, medical imaging analysis, disease detection, and health monitoring. It contains case studies and examples that show how various ML algorithms are used on biomedical data sets. The ethical issues and difficulties unique to using ML in biomedical settings, such as data privacy, algorithm bias, and regulatory compliance are also covered.Provides a broad introduction to ML in biomedicine and biomedical engineeringDiscusses ethical considerations and explainability pertinent to ML in bioengineeringExplores step-by-step tutorials, coding examples, and real-world case studiesReviews feature selection, training and evaluating models, preprocessing data, and validation techniques tailored to biomedical dataIncludes MATLAB and Python coding programsThis book is aimed at graduate students and researchers in bioengineering and ML This book combines machine learning and biomedical engineering to address practical issues in healthcare and biomedical research concentrating on real-world applications including bioinformatics, customized medicine, medical imaging analysis, disease detection, and health monitoring. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…