Explainable AI

Artificial Intelligence for Refractive Error Prediction in Children

Theodora Gianni, Anna Nikolaidou, Athanasia Sandali, Andreas Katsimpris, Ioannis D. Apostolopoulos, Lampros Lamprogiannis, Eirini Maliagkani Invest. Ophthalmol. Vis. Sci. 2026;67(7):621.

ARVO 2026 Annual Meeting — May 3-7, 2026, Denver, Colorado, USA

Artificial intelligence prediction algorithms for refractive error onset and progression in children and adolescents: A systematic review and meta‐analysis

Athanasia Sandali, Anna Nikolaidou, Theodora Gianni, Andreas Katsimpris, Ioannis D. Apostolopoulos, Lampros Lamprogiannis, Eirini Maliagkani

Acta Ophthalmologica 10.1111/aos.70207

Best Oral Presentation Award

21st Vitreous Retina Conference, 29-31 January, 2026, Athens, Greece Chatzara A., et al., Μελέτη της απόδοσης των μοντέλων τεχνητής νοημοσύνης…

Clinician-Centered Evaluation Framework for Explainable AI Heatmaps in OCT-Based Retinal Disease Classification

Eirini Maliagkani, Ilias Georgalas, Ioannis Datseris, Elpiniki Papageorgiou, Ioannis D. Apostolopoulos

Journal of Imaging — Vol. 12, No. 5, pp. 211 10.3390/jimaging12050211

Explainable Deep Learning Self-Supervised Vision Transformer for Fundus-Based Myopia Classification

Eirini Maliagkani, Christos Tsoutsas, Nikolaos Papageorgiou, Ioannis D. Apostolopoulos, Nikolaos Papandrianos, Ilias Georgalas, Elpiniki Papageorgiou

Acta Ophthalmologica 10.1111/aos.70205

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

Explainable YOLOv8 model for solitary pulmonary nodules classification using positron emission tomography and computed tomography scans

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

Journal of Intelligent Systems — Vol. 35, No. 1 10.1515/jisys-2025-0064

ΜΕΛΕΤΗ ΤΗΣ ΑΠΟΔΟΣΗΣ ΤΩΝ ΜΟΝΤΕΛΩΝ ΤΕΧΝΗΤΗΣ ΝΟΗΜΟΣΥΝΗΣ ΣΤΟ SEGMENTATION ΤΗΣ ΓΕΩΓΡΑΦΙΚΗΣ ΑΤΡΟΦΙΑΣ

Maliagkani E., et al.

21ο Πανελλήνιο Συνέδριο Υαλοειδούς Αμφιβληστροειδούς (GVRS 2026) — January 29-31, Athens, Greece

A machine learning approach for determining solitary pulmonary nodule malignancy in patients undergoing PET/CT examination

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

Multimedia Tools and Applications — Vol. 84, No. 32, pp. 39905-39924 10.1007/s11042-025-20737-x

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

Artificial Intelligence Algorithms for Epiretinal Membrane Detection, Segmentation and Postoperative BCVA Prediction: A Systematic Review and Meta-Analysis

Eirini Maliagkani, Petroula Mitri, Dimitra Mitsopoulou, Andreas Katsimpris, Ioannis D. Apostolopoulos, Athanasia Sandali, Konstantinos Tyrlis, Nikolaos Papandrianos, Ilias Georgalas

Applied Sciences — Vol. 15, No. 22, pp. 12280 10.3390/app152212280

Improving Real-time High-Resolution Estimates of PM2.5 Concentration Fields in Urban Areas by the SmartAQ+ System with Data Fusion and Machine Learning

Apostolopoulos I.D., Siouti E., Fouskas G., Pandis S.N.

Atmospheric Environment — 364 10.1016/j.atmosenv.2025.121665

Improving Real-time High-Resolution Estimations of PM2.5 Concentration Fields for the present time in Urban Areas by the SmartAQ+ System with Data Fusion and Machine Learning

C-STACC Seminar — Patras, Greece

Neural-FCM: a deep learning approach for weight matrix optimization in Fuzzy Cognitive Map classifiers

Theodoros Tziolas, Konstantinos Papageorgiou, Ioannis Apostolopoulos, Elpiniki Papageorgiou

Applied Intelligence — Vol. 55, No. 13 10.1007/s10489-025-06795-6

The Role of Artificial Intelligence in the Diagnosis, Segmentation, and Prediction of Retinal Vein Occlusion: A Systematic Review

Eirini Maliagkani, Vyron Michalakis, Ioannis D Apostolopoulos, Konstantinos Tyrlis, Ilias Georgalas

Cureus 10.7759/cureus.97419

Utility of disease probability scores to guide decision-making during screening for phaeochromocytoma and paraganglioma: a machine learning modelling cross sectional study

Christina Pamporaki, Georg Pommer, Ioannis D. Apostolopoulos, Angelos Filippatos, Mirko Peitzsch, Hanna Remde, Georgiana Constantinescu, Annika M.A. Berends, Matthew A. Nazari, Felix Beuschlein, Martin Fassnacht, Aleksander Prejbisz, Karel Pacak, Graeme Eisenhofer

eClinicalMedicine — Vol. 82, pp. 103181 10.1016/j.eclinm.2025.103181

A Medical Decision Support System (MDSS) for Explainable Multimodal Detection of Non-Small Cell Lung Cancer Using Clinical and PET Data

Anna Feleki, Nikolaos Papandrianos, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Nikolaos Papathanasiou, Dimitrios Apostolopoulos, Jose Maria Alonso Moral, Javier Andreu-Perez

EXPLAINABILITY 2024 10.5281/zenodo.14631853

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

Investigating the agreement with human readers and generalisation capabilities of a transfer learning approach for predicting the malignancy of Solitary Pulmonary Nodules in CT screening

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

IISA 2024 10.1109/IISA62523.2024.10786628

Medical Decision Support System in Nuclear Medicine Diagnosis for Non-Small Cell Lung Cancer and Coronary Artery Disease: A First Stage Prototype

Agorastos-Dimitrios Samaras, Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, Elpiniki Papageorgiou, Konstantinos Kokkinos, Nikolaos Papandrianos

IISA 2024 10.1109/IISA62523.2024.10786612

Multimodal Diagnosis using Deep Fuzzy Cognitive Map with Extreme Learning Machine Integrated into a Medical Decision Support System for Coronary Artery Disease and Non-Small Cell Lung Cancer Detection

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

28th Pan-Hellenic Conference on Informatics (PCI 2024) 10.1145/3716554.3716615

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 Fuzzy Cognitive Map methodology for Non-Small Cell Lung Cancer diagnosis based on Positron Emission Tomography imaging

Anna Feleki, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Serafeim Moustakidis, Nikolaos D Papathanasiou, Dimitris J Apostolopoulos, Konstantinos Kokkinos, Nikolaos Papandrianos

IISA 2023 10.1109/IISA59645.2023.10345912

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

Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism

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

Algorithms — Vol. 16, No. 9, pp. 435 10.3390/a16090435

Explainable Classification for Non-Small Cell Lung Cancer based on Positron Emission Tomography features and clinical data

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

IISA 2023 10.1109/IISA59645.2023.10345893

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

Fuzzy Cognitive Maps: Their Role in Explainable Artificial Intelligence

Ioannis D. Apostolopoulos, Peter P. Groumpos

Applied Sciences — Vol. 13, No. 6, pp. 3412 10.3390/app13063412

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

A Deep Learning Methodology for the Detection of Abnormal Parathyroid Glands via Scintigraphy with 99mTc-Sestamibi

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

Diseases — Vol. 10, No. 3, pp. 56 10.3390/diseases10030056

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

An Explainable Deep Learning Framework for Detecting and Localising Smoke and Fire Incidents: Evaluation of Grad-CAM++ and LIME

Ioannis D. Apostolopoulos, Ifigeneia Athanasoula, Mpesi Tzani, Peter P. Groumpos

Machine Learning and Knowledge Extraction — Vol. 4, No. 4, pp. 1124-1135 10.3390/make4040057

Artificial Intelligence Methods for Identifying and Localizing Abnormal Parathyroid Glands: A Review Study

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

Machine Learning and Knowledge Extraction — Vol. 4, No. 4, pp. 814-826 10.3390/make4040040

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

Deep learning for the detection and localization of abnormal parathyroid glands in patients with hyperparathyroidism

Ioannis D. Apostolopoulos, Nikolaos Papathanasiou, George Panayiotakis, Dimitris Apostolopoulos

1st Panhellenic Conference of Medical Physics 10.1016/S1120-1797(22)03068-X

Deep Learning Methods to Reveal Important X-ray Features in COVID-19 Detection: Investigation of Explainability and Feature Reproducibility

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

Reports — Vol. 5, No. 2, pp. 20 10.3390/reports5020020

Detection and Localisation of Abnormal Parathyroid Glands: An Explainable Deep Learning Approach

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

Algorithms — Vol. 15, No. 12, pp. 455 10.3390/a15120455

Evaluation of Grad-CAM for explaining Deep Learning’s decisions on various medical imaging datasets

Ifigeneia Athanasoula, Ioannis D. Apostolopoulos, Peter P Groumpos

UBT INTERNATIONAL CONFERENCE 2022RESILIENCE, INNOVATION, AND SUSTAINABILITY 10.33107/ubt-ic.2022.283

Explainable Deep Learning for localising abnormal Parathyroid Glands in parathyroid scintigraphy

Ioannis D. Apostolopoulos, Apostolopoulos Dimitris, Spyridonidis Trifon, Panayiotakis George S

Edge Intelligence 2022 10.63438/NWSS8207

Fuzzy Cognitive Maps and Explainable Artificial Intelligence: a critical perspective

Ifigeneia Athanasoula, Ioannis D. Apostolopoulos, Peter P Groumpos

UBT INTERNATIONAL CONFERENCE 2022RESILIENCE, INNOVATION, AND SUSTAINABILITY 10.33107/ubt-ic.2022.281

Intelligent Modeling for the food chain using Fuzzy Cognitive Maps

Ifigeneia Athanasoula, Ioannis D. Apostolopoulos, Peter P Groumpos

UBT INTERNATIONAL CONFERENCE 2022RESILIENCE, INNOVATION, AND SUSTAINABILITY 10.33107/ubt-ic.2022.282

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

Modeling the spread of dangerous pandemics with the utilization of a hybrid-statistical–Advanced-Fuzzy-Cognitive-Map algorithm: the example of COVID-19

Peter P. Groumpos, Ioannis D. Apostolopoulos

Research on Biomedical Engineering — Vol. 37, No. 4, pp. 749-764 10.1007/s42600-021-00182-z

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 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

Diagnostics

Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou and George S. Panayiotakis

Diagnostics 10.3390/diagnostics