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Smart Biosensing Technologies for Early Detection of Metabolic Disorders
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Form:Einzelkauf Download
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Sprache:Englisch
185,99 €
inkl. gesetzl. MwSt.Artikel erhalten
Beschreibung
Produktdetails
Format
ePUB
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
07.08.2026
Verlag
Elsevier Science & Techn.Seitenzahl
400 (Printausgabe)
Dateigröße
113656 KB
Sprache
Englisch
EAN
9780443459122
Smart Biosensing Technologies for Early Detection of Metabolic Disorders gives a clear overview of the latest biosensor tools that help detect and monitor metabolic diseases like diabetes, obesity, and insulin resistance early. It explains how these sensors work using basic science and shows new wearable, non-invasive, and easy-to-use devices. This book is useful for researchers, doctors, and professionals working in healthcare technology. This book connects research from different fields to help solve real problems in making and using biosensors. It includes examples of how these sensors are used, new markers for disease detection, and how AI and digital health can improve care. Readers will learn how to develop better diagnostic tools and improve treatment for metabolic diseases.
- Provides comprehensive coverage of smart biosensing technologies for MDs, emphasizing biophysical mechanisms and disease-specific applications
- Includes translational case studies and practical guidance on clinical validation, reliability assessment, regulatory challenges, and commercialization pathways
- Highlights emerging biomarkers, multiomic approaches, AI-enabled biosensors, and digital health integration for personalized metabolic healthcare
- Bridges multidisciplinary perspectives from biomedical sciences, engineering, data science, and pharmaceutical innovation to support real-world clinical impact
- Provides comprehensive coverage of smart biosensing technologies for MDs, emphasizing biophysical mechanisms and disease-specific applications
- Includes translational case studies and practical guidance on clinical validation, reliability assessment, regulatory challenges, and commercialization pathways
- Highlights emerging biomarkers, multiomic approaches, AI-enabled biosensors, and digital health integration for personalized metabolic healthcare
- Bridges multidisciplinary perspectives from biomedical sciences, engineering, data science, and pharmaceutical innovation to support real-world clinical impact
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