Computational Intelligence in Healthcare Applications
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- Taschenbuch
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Form:Einzelkauf Download
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Sprache:Englisch
144,00 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
14.07.2022
Herausgeber
Rajeev Agrawal + weitereVerlag
Elsevier Science & Techn.Seitenzahl
376 (Printausgabe)
Dateigröße
26015 KB
Sprache
Englisch
EAN
9780323993746
Computational Intelligence in Healthcare Applications discusses a variety of techniques designed to represent, enhance and empower inter-domain research based on computational intelligence in healthcare. The book serves as a reference for the pervasive healthcare domain which takes into consideration new convergent computing and other applications. The book discusses topics such as mathematical modeling in medical imaging, predictive modeling based on artificial intelligence and deep learning, smart healthcare and wearable devices, and evidence-based predictive modeling. In addition, it discusses computer-aided diagnostic for clinical inferences and pervasive and ubiquitous techniques in healthcare.
This book is a valuable resource for graduate students and researchers in medical informatics, however, it is also ideal for members of the biomedical field and healthcare industry who are interested in learning more about novel technologies and their applications in the field.
- Presents advanced procedures to address and enhance available diagnostic methods
- Focuses on identifying challenges and solutions through an integrated approach that shapes a path for new research dimensions
- Discusses the implementation of deep learning techniques for the detection and classification of diseases
This book is a valuable resource for graduate students and researchers in medical informatics, however, it is also ideal for members of the biomedical field and healthcare industry who are interested in learning more about novel technologies and their applications in the field.
- Presents advanced procedures to address and enhance available diagnostic methods
- Focuses on identifying challenges and solutions through an integrated approach that shapes a path for new research dimensions
- Discusses the implementation of deep learning techniques for the detection and classification of diseases
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