Deep Learning

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 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

MedScanGAN: Synthetic PET & CT Scan Generation Using Conditional Generative Adversarial Networks for Medical AI Data Augmentation

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

Bioengineering — Vol. 13, No. 3, pp. 281 10.3390/bioengineering13030281

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 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

Forecasting PM2.5 and NO2 Concentrations in Patras Using Low-Cost Sensors and Machine Learning

Ioannis D. Apostolopoulos; George Fouskas; Spyros N. Pandis

2025 IEEE International Smart Cities Conference (ISC2) 10.1109/ISC266238.2025.11293331

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

A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination

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

Big Data and Cognitive Computing — Vol. 8, No. 8, pp. 85 10.3390/bdcc8080085

Fuzzy Cognitive Map Applications in Medicine over the Last Two Decades: A Review Study

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

Bioengineering — Vol. 11, No. 2, pp. 139 10.3390/bioengineering11020139

Integrating Machine Learning in Clinical Practice for Characterizing the Malignancy of Solitary Pulmonary Nodules in PET/CT Screening

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

Diseases — Vol. 12, No. 6, pp. 115 10.3390/diseases12060115

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 General Machine Learning Model for Assessing Fruit Quality Using Deep Image Features

Ioannis D. Apostolopoulos, Mpesi Tzani, Sokratis I. Aznaouridis

AI — Vol. 4, No. 4, pp. 812-830 10.3390/ai4040041

Abnormal Parathyroid Gland localization in scintigraphic images using a Vision Transformer network

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

IISA 2023 10.1109/IISA59645.2023.10345948

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

An Attention-Based Deep Convolutional Neural Network for Brain Tumor and Disorder Classification and Grading in Magnetic Resonance Imaging

Ioannis D. Apostolopoulos, Sokratis Aznaouridis, Mpesi Tzani

Information — Vol. 14, No. 3, pp. 174 10.3390/info14030174

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

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 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 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

Industrial object and defect recognition utilizing multilevel feature extraction from industrial scenes with Deep Learning approach

Ioannis D. Apostolopoulos, Mpesiana A. Tzani

Journal of Ambient Intelligence and Humanized Computing — Vol. 14, No. 8, pp. 10263-10276 10.1007/s12652-021-03688-7

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

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

Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review

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

European Journal of Nuclear Medicine and Molecular Imaging — Vol. 49, No. 11, pp. 3717-3739 10.1007/s00259-022-05805-w

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

Solitary Pulmonary Nodule malignancy classification utilising 3D features and semi-supervised Deep Learning

Ioannis D. Apostolopoulos, Dimitris J Apostolopoulos, George S Panayiotakis

IISA 2022 10.1109/IISA56318.2022.9904334

Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques

Ioannis D. Apostolopoulos, Emmanuel G. Pintelas, Ioannis E. Livieris, Dimitris J. Apostolopoulos, Nikolaos D. Papathanasiou, Panagiotis E. Pintelas, George S. Panayiotakis

Medical & Biological Engineering & Computing — Vol. 59, No. 6, pp. 1299-1310 10.1007/s11517-021-02378-y

Classification of lung nodule malignancy in computed tomography imaging utilising generative adversarial networks and semi-supervised transfer learning

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

Biocybernetics and Biomedical Engineering — Vol. 41, No. 4, pp. 1243-1257 10.1016/j.bbe.2021.08.006

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

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks

Ioannis D. Apostolopoulos, Tzani A. Mpesiana

Physical and Engineering Sciences in Medicine — Vol. 43, No. 2, pp. 635-640 10.1007/s13246-020-00865-4

Extracting Possibly Representative COVID-19 Biomarkers from X-ray Images with Deep Learning Approach and Image Data Related to Pulmonary Diseases

Ioannis D. Apostolopoulos, Sokratis I. Aznaouridis, Mpesiana A. Tzani

Journal of Medical and Biological Engineering — Vol. 40, No. 3, pp. 462-469 10.1007/s40846-020-00529-4

Diagnostics

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

Diagnostics 10.3390/diagnostics