Coronary Artery Disease

AIRGO Kicks Off!

AIRGO designs and builds AI systems for businesses, the public sector and research teams. Scientifically grounded, explainable, and wrapped in…

Explainable AI Suite for Nuclear Medicine

An end-to-end environment for developing and interrogating deep learning models on nuclear medicine and radiological images. It handles study import,…

Explainable Machine Learning Prognosis of Coronary Artery Disease Using Lifestyle and Medical History Data

Agorastos-Dimitrios Samaras, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Nikolaos Papandrianos

Applied Sciences — Vol. 16, No. 11, pp. 5444 10.3390/app16115444

FCM-Encoder: a novel interpretable framework with vision–language reasoning for coronary artery disease and solitary pulmonary nodule classification

Anna Feleki, Elpiniki Papageorgiou, Ioannis D. Apostolopoulos, Dimitris J. Apostolopoulos, Nikolaos Papathanasiou, Nikolaos I. Papandrianos

BMC Medical Informatics and Decision Making 10.1186/s12911-026-03695-8

XAI Suite and Evidence-based AI validation tools

A cross-domain workbench for building, explaining and — critically — validating AI models before anyone trusts them. It couples model…

A Review on SPECT Myocardial Perfusion Imaging Attenuation Correction Using Deep Learning

Ioannis D. Apostolopoulos, Nikolaοs Ι. Papandrianos, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos

Applied Sciences — Vol. 15, No. 20, pp. 11287 10.3390/app152011287

Clinical validation of the EMERALD’s MDSS t the University Hospital of Patras

On April 1st, 2025, the developed Medical Decision Support System (MDSS) was clinically validated at the University Hospital of Patras,…

Fuzzy Cognitive Explainable Analytics for Translating Model Complexity in Nuclear Medical Diagnosis (EMERALD)

EMERALD takes a unique, holistic approach to patient-specific predictive modeling and MDSS development by extracting and integrating knowledge from new…

Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis

Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Dimitrios J. Apostolopoulos and Elpiniki Papageorgiou

Bioengineering — 11(10), 957 10.3390/bioengineering11100957/s1

A Fuzzy Cognitive Map learning approach for coronary artery disease diagnosis in Nuclear Medicine

Anna Feleki, Ioannis D. Apostolopoulos, Konstantinos Papageorgiou, Elpiniki I Papageorgiou, Dimitris J Apostolopoulos, Nikolaos I Papandrianos

13th Conference of the European Society for Fuzzy Logic and Technology 10.1007/978-3-031-39965-7_2

AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: a review

Nikolaos I. Papandrianos, Ioannis D. Apostolopoulos, Anna Feleki, Serafeim Moustakidis, Konstantinos Kokkinos, Elpiniki I. Papageorgiou

Nuclear Medicine Communications — Vol. 44, No. 1, pp. 1-11 10.1097/mnm.0000000000001634

Classification models for assessing coronary artery disease instances using clinical and biometric data: an explainable man-in-the-loop approach

Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, Nikolaos Papandrianos, Elpiniki Papageorgiou

Scientific Reports — Vol. 13, No. 1 10.1038/s41598-023-33500-9

Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies

Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Anna Feleki, Serafeim Moustakidis, Elpiniki I. Papageorgiou

EJNMMI Physics — Vol. 10, No. 1 10.1186/s40658-022-00522-7

Diagnosis of Coronary Artery Disease from Myocardial Perfusion Imaging Polar Maps with an innovative attention-based feature-fusion network

Anna Feleki et al.

19th International Conference on Machine Learning and Data Mining MLDM

Explainable Deep Fuzzy Cognitive Map Diagnosis of Coronary Artery Disease: Integrating Myocardial Perfusion Imaging, Clinical Data, and Natural Language Insights

Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Nikolaos Papathanasiou, Dimitrios Apostolopoulos, Nikolaos Papandrianos

Applied Sciences — Vol. 13, No. 21, pp. 11953 10.3390/app132111953

Innovative Attention-Based Explainable Feature-Fusion VGG19 Network for Characterising Myocardial Perfusion Imaging SPECT Polar Maps in Patients with Suspected Coronary Artery Disease

Ioannis D. Apostolopoulos, Nikolaοs D. Papathanasiou, Nikolaos Papandrianos, Elpiniki Papageorgiou, Dimitris J. Apostolopoulos

Applied Sciences — Vol. 13, No. 15, pp. 8839 10.3390/app13158839

Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models

Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Nikolaos Papandrianos

Applied Sciences — Vol. 13, No. 14, pp. 8120 10.3390/app13148120

An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM

Nikolaos I. Papandrianos, Anna Feleki, Serafeim Moustakidis, Elpiniki I. Papageorgiou, Ioannis D. Apostolopoulos, Dimitris J. Apostolopoulos

Applied Sciences — Vol. 12, No. 15, pp. 7592 10.3390/app12157592

Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease

Nikolaos I. Papandrianos, Ioannis D. Apostolopoulos, Anna Feleki, Dimitris J. Apostolopoulos, Elpiniki I. Papageorgiou

Annals of Nuclear Medicine — Vol. 36, No. 9, pp. 823-833 10.1007/s12149-022-01762-4

Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic

Ioannis D. Apostolopoulos, Besiana A Tzani

IISA 2022 10.1109/IISA56318.2022.9904388

Advanced fuzzy cognitive maps: state-space and rule-based methodology for coronary artery disease detection

Ioannis D Apostolopoulos, Peter P Groumpos, Dimitris J Apostolopoulos

Biomedical Physics & Engineering Express — Vol. 7, No. 4, pp. 045007 10.1088/2057-1976/abfd83

CORONARY ARTERY DISEASE DIAGNOSIS USING MYOCARDIAL PERFUSION IMAGING POLAR MAPS AND DEEP LEARNING METHODS

15th Panhellenic Conference of Nuclear Medicine — May 27-30, 2021, Online 10.13140/RG.2.2.27879.57768

Multi-Input Deep Learning Approach for Cardiovascular Disease Diagnosis using Myocardial Perfusion Imaging and Clinical Data

Ioannis D. Apostolopoulos, Dimitris I. Apostolopoulos, Trifon I. Spyridonidis, Nikolaos D. Papathanasiou, George S. Panayiotakis

Physica Medica 10.1016/j.ejmp.2021.04.011

Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation

Ioannis D. Apostolopoulos, Nikolaos D Papathanasiou, Trifon Spyridonidis, Dimitris J Apostolopoulos

Hellenic Journal of Nuclear Medicine 10.1967/s002449912101

Non – invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps

Ioannis D. Apostolopoulos, Peter P. Groumpos

Computer Methods in Biomechanics and Biomedical Engineering — Vol. 23, No. 12, pp. 879-887 10.1080/10255842.2020.1768534

A DECISION MAKING SUPPORT SYSTEM IN NUCLEAR MEDICINE USING FUZZY COGNITIVE MAPS

Apostolopoulos I.D. et al.

7o ΠΑΝΕΛΛΗΝΙΟ ΣΥΝΕΔΡΙΟ ΒΙΟΪΑΤΡΙΚΗΣ ΤΕΧΝΟΛΟΓΙΑΣ — April 7, 2017, Athens, Greece 10.13140/RG.2.2.26912.94724

A Medical Decision Support System for the Prediction of the Coronary Artery Disease Using Fuzzy Cognitive Maps

Ioannis D. Apostolopoulos, Peter P Groumpos, Dimitris I Apostolopoulos

Creativity in Intelligent Technologies and Data Science 10.1007/978-3-319-65551-2_20