What question did this study set out to answer?

To explore how artificial intelligence can enhance the early detection of heart disease.

January 9, 2026Open Access

Artificial intelligence models, especially Convolutional Neural Networks, improve early detection of heart disease by accurately classifying arrhythmias and coronary disease.

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Key result

Authors

SRSungini Rijhwani SNS.S. Khora and Pagolu Navya NSNettem Nithya Sree

Discussion

Member takes

Overview

This analysis demonstrates improved heart disease detection through AI in ECG signals, suggesting better patient outcomes.

Key Points

To explore how artificial intelligence can enhance the early detection of heart disease.
Analysis of ECG signals using artificial intelligence techniques
Application of machine learning models like Random Forest and Support Vector Machines
Utilization of deep learning with Convolutional Neural Networks to extract cardiac features
Implementation of explainable AI methods like SHAP for clearer predictions
Machine learning and deep learning models effectively classify heart conditions like arrhythmias and coronary disease.
Explainable AI methods increase clinician confidence in AI predictions.
AI systems are becoming more robust with integrated multimodal data, enhancing clinical relevance.

Cite This Study

Rijhwani et al. (2026) studied this question. Artificial intelligence models, especially Convolutional Neural Networks, improve early detection of heart disease by accurately classifying arrhythmias and coronary disease.

synapsesocial.com/papers/696128f244c2cd6c68456c35 https://doi.org/10.5281/zenodo.18149845

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January 9, 2026Open Access

Artificial intelligence models, especially Convolutional Neural Networks, improve early detection of heart disease by accurately classifying arrhythmias and coronary disease.

View Full Paper

Ask AI

Bookmark

Key result

Artificial intelligence models, especially Convolutional Neural Networks, improve early detection of heart disease by accurately classifying arrhythmias and coronary disease.

Authors

SRSungini Rijhwani SNS.S. Khora and Pagolu Navya NSNettem Nithya Sree

Discussion

Member takes

Overview

This analysis demonstrates improved heart disease detection through AI in ECG signals, suggesting better patient outcomes.

Key Points

To explore how artificial intelligence can enhance the early detection of heart disease.
Analysis of ECG signals using artificial intelligence techniques
Application of machine learning models like Random Forest and Support Vector Machines
Utilization of deep learning with Convolutional Neural Networks to extract cardiac features
Implementation of explainable AI methods like SHAP for clearer predictions
Machine learning and deep learning models effectively classify heart conditions like arrhythmias and coronary disease.
Explainable AI methods increase clinician confidence in AI predictions.
AI systems are becoming more robust with integrated multimodal data, enhancing clinical relevance.

Cite This Study

synapsesocial.com/papers/696128f244c2cd6c68456c35 https://doi.org/10.5281/zenodo.18149845

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