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Related Concept Videos

Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

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Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
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Coronary Artery Disease III: Clinical Manifestations01:30

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Coronary Artery Disease (CAD) is a primary health risk worldwide, leading to significant morbidity and mortality. The condition arises from the buildup of atherosclerotic plaques within the coronary arteries, resulting in diminished blood supply to the heart muscle.The clinical manifestations of CAD vary widely, from asymptomatic stages to severe, life-threatening conditions. Understanding these manifestations is crucial for early diagnosis and effective management.Angina Pectoris: The Warning...
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Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
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Atherosclerosis II: Clinical Manifestations and Diagnostic Tests01:27

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Atherosclerosis is a progressive disorder that leads to the thickening and narrowing of arterial walls due to plaque buildup. This condition can cause various symptoms depending on the arteries affected:Coronary Artery Disease (CAD): This condition affects the coronary arteries and may lead to chest pain (angina), shortness of breath (dyspnea), heart attacks, and other heart disease symptoms.Cerebrovascular Disease: This affects blood flow to the brain, causing transient ischemic attacks (TIAs)...
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Peripheral Arterial Disease II: Clinical Manifestations and Diagnostic Evaluation01:21

Peripheral Arterial Disease II: Clinical Manifestations and Diagnostic Evaluation

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Clinical manifestationsPeripheral Arterial Disease (PAD) manifests through a range of symptoms, from the characteristic intermittent claudication to atypical presentations and severe complications in advanced stages. Intermittent claudication, a hallmark symptom of PAD, presents as exercise-induced muscle pain that typically resolves within minutes of rest. This pain is reproducible and stems from inadequate blood flow, leading to the accumulation of lactic acid produced during anaerobic...
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Coronary Artery Disease I: Introduction01:30

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Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
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Related Experiment Video

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Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
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Heart disease severity level identification system on Hyperledger consortium network.

Sasikumar R1, Karthikeyan P2

  • 1Computer Science and Engineering, K.Ramakrishnan College of Engineering, Tiruchirappalli, Tamilnadu, India.

Peerj. Computer Science
|October 23, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a blockchain-based system using Hyperledger and attribute-based access control (ABAC) to enhance Electronic Health Record (EHR) security and privacy. It also integrates a Gaussian Naive Bayes algorithm for cardiovascular disease prediction, improving patient care and data management.

Keywords:
Attribute based access controlBlockchainElectronic health recordEmergency attribute based access controlFeature weight computationGaussian naïve BayesHyperledger fabric

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Area of Science:

  • Health Informatics
  • Blockchain Technology
  • Data Security

Background:

  • Electronic Health Records (EHRs) are crucial for patient care but face significant privacy and security challenges.
  • Existing EHR systems struggle to provide robust protection for sensitive patient data against unauthorized access and tampering.
  • Blockchain technology offers a decentralized and immutable ledger, presenting a promising solution for secure health information management.

Purpose of the Study:

  • To develop a secure and privacy-preserving system for sharing Electronic Health Records (EHRs) using blockchain technology.
  • To implement an attribute-based access control (ABAC) mechanism for fine-grained control over EHR access.
  • To integrate a predictive model for cardiovascular disease risk assessment within the blockchain framework.

Main Methods:

  • A Hyperledger consortium network was developed for secure EHR sharing.
  • Attribute-Based Access Control (ABAC) was implemented for granular data access permissions.
  • A Gaussian Naive Bayes algorithm was integrated for cardiovascular disease prediction.
  • The system was tested using multiple medical datasets (heart disease, diabetes, stroke, body fat) from Kaggle.
  • Performance was evaluated using Hyperledger Caliper, measuring metrics like latency and transaction rate.

Main Results:

  • The developed Hyperledger network successfully enhanced privacy and security for EHR sharing.
  • ABAC provided precise control over access to sensitive health records based on user attributes.
  • The integrated Gaussian Naive Bayes algorithm demonstrated effectiveness in predicting cardiovascular disease risk.
  • Performance benchmarks showed efficient transaction rates and resource utilization.

Conclusions:

  • The proposed blockchain-based system effectively addresses privacy and security concerns in EHR management.
  • Attribute-Based Access Control significantly improves the security posture of health information systems.
  • The integration of predictive analytics enhances clinical decision-making and patient risk stratification.
  • This approach offers a robust framework for secure, efficient, and intelligent health record management.