Machine Learning in Cardiovascular Risk Diagnosis: -Neuro-Fuzzy Based Atherosclerotic-CV Risk Prediction Model Using Non-Traditional US Image Markers - Image 1

£81.99

About as cheap as it gets — within 5% of the all-time low it hit 1 month ago.

£82 today · all-time low £81 (Sep 2026) · usually £82

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

Name: Machine Learning in Cardiovascular Risk Diagnosis: -Neuro-Fuzzy Based Atherosclerotic-CV Risk Prediction Model Using Non-Traditional US Image Markers
Brand: LAP Lambert Academic Publishing
Price: 81.99 GBP
Availability: InStock

Higher Education

Price data last checked 23 day(s) ago - will refresh soon

View at Amazon

We'll watch every seller, every day. One email when your price arrives.

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 68 days · 68 data points (no recent data)

Price data last checked 23 day(s) ago - will refresh soon

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↑ Price chart
when this has been cheap or pricey

↑ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price Distribution

Price distribution over 68 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £82 (52 days, 76.5%)

Price range: £81 - £82

Price levels: 2 different prices over 68 days

Description

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.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 6208415527
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Education > Higher Education
Domain: Amazon UK
Release Date: 12 March 2025
Listed Since: 06 April 2025

Barcode

No barcode data available

About as cheap as it gets — within 5% of the all-time low it hit 1 month ago.

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

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Korrektsiya endotelial'noy disfunktsii: pri ateroskleroze arteriy nizhnikh konechnostey

Dietary Risk Factors of Cardiovascular Diseases (Cardiology Research and Clinical Developments)

A Novel Framework for the Modeling of Cardiac Electrophysiology: with Application to Ischemia Detection and Infarction Localization

Deep Learning for Cardiac Signal Analysis in Robotic Applications (Medical Robotics and Computer Assisted Surgery: AI-enhanced, Data-driven, and Evidence-based Approaches)

Cardiovascular Risk Factors

Risk Factors for Cardiovascular Disease

Prevalence of coronary risk factors in pre and post menopausal women

Cardiovascular Risk Factors and Intervention Strategies for the Prevention of Cardiovascular Disease

Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare

DEEP LEARNING FOR HEALTHCARE: AI IN DIAGNOSIS, IMAGING, AND GENOMIC

AI-Powered COVID-19 Prediction: A Comprehensive Framework for Severity Assessment Using Deep Learning and Medical Imaging

Depression and Coronary Artery Disease: Prevalence of Coronary Artery Disease (CAD) Risk Factors in Depressed Retired Population

Myocardial Injury Effects of Gender, Local Anesthesia and Antioxidant

Isoprenoid Organism, Cholesterol and Human Evolution

Imagerie cardiaque: Imagerie en coupes : scanner, IRM

Imaging Coronary Atherosclerosis (Contemporary Cardiology)

Navigating Cardiology's Future: AI in MRI Imaging and Outcome Projections

Cardiac Rehabilitation: An Educational Intervention Module for Registered Nurses in India

Practical Cardiovascular Medicine

ECG Monitoring for Detection of Arrhythmias & Compression Techniques: Minimization of Storage Requirements

Artificial Intelligence of Medicine: Modern Computational Methods for Personalized Cardiovascular Risk Assessment and Treatment

Non-invasive assessment of central arterial pulses with optical fibres

Advances in Clinical Cardiovascular Imaging, Echocardiography & Interventions: A Textbook of Cardiology

Cardiac Diseases: Novel Aspects of Cardiac Risk, Cardiorenal Pathology and Cardiac Interventions

About as cheap as it gets — within 5% of the all-time low it hit 1 month ago.

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

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Korrektsiya endotelial'noy disfunktsii: pri ateroskleroze arteriy nizhnikh konechnostey

Dietary Risk Factors of Cardiovascular Diseases (Cardiology Research and Clinical Developments)

A Novel Framework for the Modeling of Cardiac Electrophysiology: with Application to Ischemia Detection and Infarction Localization

Deep Learning for Cardiac Signal Analysis in Robotic Applications (Medical Robotics and Computer Assisted Surgery: AI-enhanced, Data-driven, and Evidence-based Approaches)

Cardiovascular Risk Factors

Risk Factors for Cardiovascular Disease

Prevalence of coronary risk factors in pre and post menopausal women

Cardiovascular Risk Factors and Intervention Strategies for the Prevention of Cardiovascular Disease

Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare

DEEP LEARNING FOR HEALTHCARE: AI IN DIAGNOSIS, IMAGING, AND GENOMIC

AI-Powered COVID-19 Prediction: A Comprehensive Framework for Severity Assessment Using Deep Learning and Medical Imaging

Depression and Coronary Artery Disease: Prevalence of Coronary Artery Disease (CAD) Risk Factors in Depressed Retired Population

Myocardial Injury Effects of Gender, Local Anesthesia and Antioxidant

Isoprenoid Organism, Cholesterol and Human Evolution

Imagerie cardiaque: Imagerie en coupes : scanner, IRM

Imaging Coronary Atherosclerosis (Contemporary Cardiology)

Navigating Cardiology's Future: AI in MRI Imaging and Outcome Projections

Cardiac Rehabilitation: An Educational Intervention Module for Registered Nurses in India

Practical Cardiovascular Medicine

ECG Monitoring for Detection of Arrhythmias & Compression Techniques: Minimization of Storage Requirements

Artificial Intelligence of Medicine: Modern Computational Methods for Personalized Cardiovascular Risk Assessment and Treatment

Non-invasive assessment of central arterial pulses with optical fibres

Advances in Clinical Cardiovascular Imaging, Echocardiography & Interventions: A Textbook of Cardiology

Cardiac Diseases: Novel Aspects of Cardiac Risk, Cardiorenal Pathology and Cardiac Interventions