Innovative feature selection and classification model for heart disease prediction

Article Computer Science, Artificial Intelligence

An Innovative Risk Assessment Methodology for Medical Information Systems

Antonio Coronato et al.

Summary: Modern medical information systems and devices require stringent risk management activities to ensure safety. The current risk management standard, ISO 14971, is not suitable for modern medical information systems and lacks a quantitative analysis method. This paper proposes a dynamic probabilistic risk assessment methodology that complies with ISO 14971 and allows for quantitative analysis considering the temporal dimension.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2022)

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Article Computer Science, Interdisciplinary Applications

An hybrid ECG-based deep network for the early identification of high-risk to major cardiovascular events for hypertension patients

Giovanni Paragliola et al.

Summary: This study proposes a novel time series-based approach that can accurately distinguish cardiovascular high-risk and low-risk hypertensive patients through the analysis of electrocardiographic holter signals. The experimental results demonstrate excellent classification accuracy with an average accuracy of 98%.

JOURNAL OF BIOMEDICAL INFORMATICS (2021)

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Article Automation & Control Systems

Machine Learning Assisted Information Management Scheme in Service Concentrated IoT

Gunasekaran Manogaran et al.

Summary: This article proposes a machine learning aided information management scheme to enhance the efficiency of IoT service data management and ensure uninterrupted user request service. The scheme utilizes a neural learning process in the data plane to control resource allocation, improving service accuracy and efficiency.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

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Article Construction & Building Technology

Effective task scheduling algorithm with deep learning for Internet of Health Things (IoHT) in sustainable smart cities

Senthil Murugan Nagarajan et al.

Summary: In this study, a novel method integrating IoT and deep learning concepts for remote health monitoring and data analysis is proposed, which accumulates real-time healthcare data through cloud network architecture and analyzes it using deep learning algorithm on a medical platform. The proposed framework not only analyzes healthcare data but also provides immediate relief measures for patients in critical conditions.

SUSTAINABLE CITIES AND SOCIETY (2021)

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Article Engineering, Multidisciplinary

Feature selection model for healthcare analysis and classification using classifier ensemble technique

Senthil Murugan Nagarajan et al.

Summary: The study developed a hybrid model based on genetic algorithm and artificial bee colony algorithm for feature selection and classification of heart disease, achieving over 90% classification accuracy.

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT (2021)

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Article Computer Science, Information Systems