Machine Learning in Cardiovascular Risk Diagnosis : Neuro-Fuzzy Based Atherosclerotic-CV Risk Prediction Model Using Non-Traditional US Image Markers

Language: English

Published by LAP LAMBERT Academic Publishing, 2025

6208415527 / 9786208415525

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  • New
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Accurate quantification of ASCVD risk is essential for early and effective cardiovascular risk management. Conventional models rely solely on traditional risk factors (TRFs). These often fail to incorporate newer, non-traditional risk variables, leading to potential underestimation or overestimation of risk, especially across diverse ethnic populations. This book introduces a novel machine learning (ML)-based framework that integrates TRFs with non-traditional ultrasound-based markers like carotid intima-media thickness (cIMT) and carotid plaque (cP) features, to enhance the predictive accuracy. It covers the development of a diagnostic architecture that uses hybrid intelligent models optimized using different Meta-heuristic algorithms. The chosen framework has the advantage due to the ability to include additional newer risk variables without methodological reconstruction and thereby contribute to the development of reliable, efficient, and customizable solutions for ASCVD risk prediction in public healthcare settings.…

Seller Inventory # 9786208415525

Title
Machine Learning in Cardiovascular Risk Diagnosis : Neuro-Fuzzy Based Atherosclerotic-CV Risk Prediction Model Using Non-Traditional US Image Markers
Author
Priestly B. Shan
Publisher
LAP LAMBERT Academic Publishing
Publication year
2025
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6208415527
ISBN 13
9786208415525
Item weight
489 grams
Dimensions
220x150x20 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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First itemUS$ 39.38US$ 50.64
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