EMERALD in Scientific Peer Reviewed Journals
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Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease -
Classification models for assessing coronary artery disease instances using clinical and biometric data: an explainable man-in-the-loop approach -
Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies -
AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review -
An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM -
Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models
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Explainable Deep Fuzzy Cognitive Map Diagnosis of Coronary Artery Disease: Integrating Myocardial Perfusion Imaging, Clinical Data, and Natural Language Insights
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Innovative Attention-Based Explainable Feature-Fusion VGG19 Network for Characterising Myocardial Perfusion Imaging SPECT Polar Maps in Patients with Suspected Coronary Artery Disease
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Deep Learning Assessment for Mining Important Medical Image Features of Various Modalities -
Artificial Intelligence Methods for Identifying and Localizing Abnormal Parathyroid Glands: A Review Study -
Fuzzy Cognitive Map Applications in Medicine over the Last Two Decades: A Review Study -
Integrating Machine Learning in Clinical Practice for Characterizing the Malignancy of Solitary Pulmonary Nodules in PET/CT Screening -
A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination
EMERALD Conference Proceedings
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A Convolutional Neural Network-based explainable classification method of SPECT myocardial perfusion images in nuclear cardiology -
A Convolutional Neural Network model for SPECT Myocardial Perfusion Images Classification -
Deep learning for automatic diagnosis of coronary artery disease using SPECT MPI images -
Explainable prediction of coronary artery disease in nuclear medical imaging using deep learning
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A Fuzzy Cognitive Map learning approach for coronary artery disease diagnosis in Nuclear Medicine -
Explainable Classification for Non-Small Cell Lung Cancer based on Positron Emission Tomography features and clinical data -
Deep Fuzzy Cognitive Map methodology for Non-Small Cell Lung Cancer diagnosis based on Positron Emission Tomography imaging
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Diagnosis of Coronary Artery Disease from Myocardial Perfusion Imaging Polar Maps with an innovative attention-based feature-fusion network
