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XAI Framework for Cardiovascular Disease Prediction Using Classification Techniques
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Enhancing Cardiac AI Explainability Through Ontology-Based Evaluation
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Crop Recommender System Based on Ensemble Classifiers
inferred← citeshttps://doi.org/10.1109/incacct61598.2024.10551212openalex-snapshot
Risk Prediction of Heart Disease using Deep SHAP Techniques
inferred← citeshttps://doi.org/10.1109/incip64058.2025.11018902openalex-snapshot
A Systematic Literature Review on Machine Learning Techniques for Heart Disease Prediction
inferred← citeshttps://doi.org/10.1109/iscon57294.2023.10112052openalex-snapshot
Cardiovascular Disease Prediction Using Machine Learning
inferred← citeshttps://doi.org/10.1109/iscv60512.2024.10620154openalex-snapshot
Process Quality Assurance of Artificial Intelligence in Medical Diagnosis
inferred← citeshttps://doi.org/10.1109/isemantic67418.2025.11291855openalex-snapshot
Performance Evaluation of SHAP and LIME for Cardiovascular Disease Prediction Using an XAI Framework
inferred← citeshttps://doi.org/10.1109/qpain66474.2025.11172023openalex-snapshot
Explainable Artificial Intelligence for Heart Disease Prediction: A SHAP and LIME-Based Approach
inferred← citeshttps://doi.org/10.1109/qpain69676.2026.11546571openalex-snapshot
XAI-Driven Heterogeneous Ensemble Framework for Early Heart Failure Detection: Balancing Accuracy with Clinical Transparency
inferred← citeshttps://doi.org/10.1109/sipaim62974.2024.10783539openalex-snapshot
On the Interpretability of AI Cardiovascular Risk Models
inferred← citeshttps://doi.org/10.1109/tnse.2026.3683944openalex-snapshot
Privacy-Aware Blockchain Approach for Efficient and Secure E-Health Applications
inferred← citeshttps://doi.org/10.1142/s2972370123500034openalex-snapshot
A Comparative Study of Machine Learning Algorithms Using Explainable Artificial Intelligence System for Predicting Liver Disease
inferred← citeshttps://doi.org/10.1145/3629188.3629193openalex-snapshot
Unveiling Key Predictors for Early Heart Attack Detection using Machine Learning and Explainable AI Technique with LIME
inferred← citeshttps://doi.org/10.1145/3700794.3700820openalex-snapshot
AI4Bangladesh: AI Ethics for Bangladesh - Challenges, Risks, Principles, and Suggestions
inferred← citeshttps://doi.org/10.1145/3709367openalex-snapshot
Explainable Artificial Intelligence for Medical Applications: A Review
inferred← citeshttps://doi.org/10.1177/20552076251355669openalex-snapshot
The application of explainable artificial intelligence in the prediction, diagnoses, treatment, and management of chronic diseases: A systematic review
inferred← citeshttps://doi.org/10.1186/s12911-026-03626-7openalex-snapshot
Predicting mortality risk in hospitalized ACS patients with hypertensive comorbidity: an interpretable machine learning approach
inferred← citeshttps://doi.org/10.1186/s13000-025-01686-3openalex-snapshot
Fostering trust and interpretability: integrating explainable AI (XAI) with machine learning for enhanced disease prediction and decision transparency
inferred← citeshttps://doi.org/10.1186/s40537-023-00817-1openalex-snapshot
Advanced machine learning techniques for cardiovascular disease early detection and diagnosis
inferred← citeshttps://doi.org/10.1186/s43067-025-00273-2openalex-snapshot
Empowering text classification with NLP and explainable AI for enhanced interpretability
inferred← citeshttps://doi.org/10.1371/journal.pone.0311719openalex-snapshot
Machine learning-based risk prediction for major adverse cardiovascular events in a Brazilian hospital: Development, external validation, and interpretability
inferred← citeshttps://doi.org/10.1371/journal.pone.0311879openalex-snapshot
RETRACTED: An inherently interpretable deep learning model for local explanations using visual concepts
inferred← citeshttps://doi.org/10.1371/journal.pone.0324485openalex-snapshot
AMD-FV: Adaptive margin loss and dual path network+ for deep face verification
inferred← citeshttps://doi.org/10.14569/ijacsa.2024.01506149openalex-snapshot
Design and Development of an Efficient Explainable AI Framework for Heart Disease Prediction
inferred← citeshttps://doi.org/10.1515/cmb-2024-0004openalex-snapshot
Augmenting heart disease prediction with explainable AI: A study of classification models
inferred← citeshttps://doi.org/10.15379/ijmst.v10i1.3410openalex-snapshot
A Novel Heart Disease Prediction System using Deep Multi-Layer Perceptron and Optimal Feature Selection Mechanism
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3556482/v1openalex-snapshot
Global Shapley Explanations and LIME on HLA-B27 Positivity in Ankylosing Spondylitis Patients
inferred← citeshttps://doi.org/10.2139/ssrn.5390703openalex-snapshot
Predicting Hla-B27 Positivity in Ankylosing Spondylitis Using Explainable Artificial Intelligence: A Comprehensive Analysis
inferred← citeshttps://doi.org/10.2174/0126662558285074231120063921openalex-snapshot
Amalgamation of Transfer Learning and Explainable AI for Internet of Medical Things
inferred← citeshttps://doi.org/10.2196/39862openalex-snapshot
Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study
inferred← citeshttps://doi.org/10.23919/ccc64809.2025.11179233openalex-snapshot
Exploring Heart-Disease Risk Factors with Random Forest Analysis and Shapley Values: An ECG-Based Study
inferred← citeshttps://doi.org/10.30574/ijsra.2024.13.2.2590openalex-snapshot
Decision trees' viability and efficiency in forecasting coronary heart disease
inferred← citeshttps://doi.org/10.31083/j.fbl2810248openalex-snapshot
A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool
inferred← citeshttps://doi.org/10.32628/cseit2511620openalex-snapshot
A Comprehensive Survey of Machine Learning and Deep Learning Methods for Cardiovascular Disease Classification
inferred← citeshttps://doi.org/10.3389/fcvm.2024.1365481openalex-snapshot
Advanced detection of coronary artery disease via deep learning analysis of plasma cytokine data
inferred← citeshttps://doi.org/10.3389/fdgth.2025.1612915openalex-snapshot
Heart disease prediction with a feature-sensitized interpretable framework for the Internet of Medical Things sensors
inferred← citeshttps://doi.org/10.3389/fimmu.2025.1640904openalex-snapshot
The oral microbiome and atherosclerosis: current evidence on association, mechanisms, and clinical implications
inferred← citeshttps://doi.org/10.3389/frai.2025.1583459openalex-snapshot
A comprehensive review of machine learning for heart disease prediction: challenges, trends, ethical considerations, and future directions
inferred← citeshttps://doi.org/10.3389/frai.2026.1812622openalex-snapshot
An explainable machine learning framework for cardiovascular risk prediction using structured health data
inferred← citeshttps://doi.org/10.3390/ani15020126openalex-snapshot
From Prediction to Precision: Explainable AI-Driven Insights for Targeted Treatment in Equine Colic
inferred← citeshttps://doi.org/10.3390/bioengineering12101127openalex-snapshot
AI-RiskX: An Explainable Deep Learning Approach for Identifying At-Risk Patients During Pandemics
inferred← citeshttps://doi.org/10.3390/ecsa-10-16237openalex-snapshot
A Secure Remote Health Monitoring for Heart Disease Prediction Using Machine Learning and Deep Learning Techniques in Explainable Artificial Intelligence Framework
inferred← citeshttps://doi.org/10.3390/info15070394openalex-snapshot
Optimized Ensemble Learning Approach with Explainable AI for Improved Heart Disease Prediction
inferred← citeshttps://doi.org/10.3390/pr11041210openalex-snapshot
Enhancing Heart Disease Prediction Accuracy through Machine Learning Techniques and Optimization
inferred← citeshttps://doi.org/10.3390/sci7010014openalex-snapshot
Deep Q-Network (DQN) Model for Disease Prediction Using Electronic Health Records (EHRs)
inferred← citeshttps://doi.org/10.3390/su15043017openalex-snapshot
A Software Framework for Predicting the Maize Yield Using Modified Multi-Layer Perceptron
inferred← citeshttps://doi.org/10.34133/space.0255openalex-snapshot
Developing Explainable Artificial Intelligence Models for Space Science Applications
inferred← citeshttps://doi.org/10.36227/techrxiv.24573304openalex-snapshot
A Review of Evaluation Approaches for Explainable AI With Applications in Cardiology
inferred← citeshttps://doi.org/10.36227/techrxiv.24573304.v1openalex-snapshot
A Review of Evaluation Approaches for Explainable AI With Applications in Cardiology
inferred← citeshttps://doi.org/10.4018/979-8-3693-5468-1.ch011openalex-snapshot
Exploring Explainable AI in Healthcare
inferred← citeshttps://doi.org/10.46855/energy-proceedings-11035openalex-snapshot
Evaluation of Explainable Deep Learning Models in Predicting Hydrogen Production
inferred← citeshttps://doi.org/10.46855/energy-proceedings-11081openalex-snapshot
Security Concerns for Using Deep Learning Models in Predicting Hydrogen Production: A Comparative Study on Adversarial Attack
inferred← citeshttps://doi.org/10.47134/pslse.v2i3.386openalex-snapshot
Classification Of Heart Disease Using Feature Selection and Machine Learning Techniques
inferred← citeshttps://doi.org/10.56155/978-81-975670-5-6-11openalex-snapshot
Impact of Interpretability on Bias in ECG-Based Models for Cardiac Disease Detection
inferred← citeshttps://doi.org/10.59018/1025194openalex-snapshot
Comprehensive machine learning models for effective Cardiovascular Disease prediction
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