Machine Learning

A Machine Learning High-Resolution PM 2.5 Forecast Model (SmartAQ 2+ ) Fusing Chemical Transport Model Predictions and Low-Cost Sensor Measurements

Ioannis D. Apostolopoulos, Evangelia Siouti, George Fouskas, Spyros N. Pandis

ACS ES&T Air 10.1021/acsestair.6c00113

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…

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

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 Approaches for Geographic Atrophy Segmentation: A Systematic Review and Meta-Analysis

Aikaterini Chatzara, Eirini Maliagkani, Dimitra Mitsopoulou, Andreas Katsimpris, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Ilias Georgalas

Bioengineering — Vol. 12, No. 5, pp. 475 10.3390/bioengineering12050475

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

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

Monitoring of Indoor Air Quality in a Classroom Combining a Low-Cost Sensor System and Machine Learning

Ioannis D. Apostolopoulos, Eleni Dovrou, Silas Androulakis, Katerina Seitanidi, Maria P. Georgopoulou, Angeliki Matrali, Georgia Argyropoulou, Christos Kaltsonoudis, George Fouskas, Spyros N. Pandis

Chemosensors — Vol. 13, No. 4, pp. 148 10.3390/chemosensors13040148

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

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

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

Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning

Ioannis D. Apostolopoulos, Silas Androulakis, Panayiotis Kalkavouras, George Fouskas, Spyros N. Pandis

Sensors — Vol. 24, No. 13, pp. 4110 10.3390/s24134110

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

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

Machine Learning in Air Quality: Overview of applications and a case study on the SmartAQ forecasting system

C-STACC Seminar — Patras, Greece

Monitoring the air quality inside a classroom using multiple low-cost sensors

C-STACC Seminar — Patras, Greece

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

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

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

Development and calibration of an Air Quality Monitoring (AQM) appliance based on low-cost electrochemical and laser sensors

C-STACC Seminar — Patras, Greece

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

Field Calibration of a Low-Cost Air Quality Monitoring Device in an Urban Background Site Using Machine Learning Models

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

Atmosphere — Vol. 14, No. 2, pp. 368 10.3390/atmos14020368

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

Prediction of the Concentration and Source Contributions of PM2.5 and Gas-Phase Pollutants in an Urban Area with the SmartAQ Forecasting System

Evangelia Siouti, Ksakousti Skyllakou, Ioannis Kioutsioukis, David Patoulias, Ioannis D. Apostolopoulos, George Fouskas, Spyros N. Pandis

Atmosphere — Vol. 15, No. 1, pp. 8 10.3390/atmos15010008

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

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 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

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

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

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