PUBLICATIONS

PEER-REVIEWED SCIENTIFIC JOURNALS

[P1].

Apostolopoulos ID, Aznaouridis SI, Tzani MA. Extracting Possibly Representative COVID-19 Biomarkers from X-ray Images with Deep Learning Approach and Image Data Related to Pulmonary Diseases. J Med Biol Eng. 2020 🔓

[P2].

Apostolopoulos ID, Groumpos PP. Non - invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps. Computer Methods in Biomechanics and Biomedical Engineering. 2020 🔓

[P3].

Apostolopoulos ID, Tzani MA. Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks. Phys Eng Sci Med. 2020 🔓

[P4].

Apostolopoulos ID, Papathanasiou ND, Spyridonidis T, Apostolopoulos DJ. Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation, Hellenic Journal of Nuclear Medicine. 2020 🔓

[P5].

Apostolopoulos ID, Papathanasiou ND, Spyridonidis T, Apostolopoulos DJ, Panayiotakis G. Multi-Input Deep Learning Approach for Cardiovascular Disease Diagnosis using Myocardial Perfusion Imaging and Clinical Data, European Journal of Medical Physics. 2021 🔓

[P6].

Apostolopoulos ID, Groumpos PP, Apostolopoulos DJ. Advanced fuzzy cognitive maps: state space and rule-based methodology for coronary artery disease detection, Biomedical Physics & Engineering Express. 2021 🔓

[P7].

Apostolopoulos ID, Pintelas GE, Livieris EI, Apostolopoulos DJ, Papathanasiou DN, Pintelas EP, Panayiotakis SG. Automatic Classification of Solitary Pulmonary Nodules in PET/CT imaging employing Transfer Learning techniques, Med Biol Eng Comput. 2021 🔓

[P8].

Apostolopoulos ID, Papathanasiou ND, Panayiotakis GS. Classification of lung nodule malignancy in computed tomography imaging utilising generative adversarial networks and semi-supervised transfer learning, Biocybernetics and Biomedical Engineering. 2021 🔓

[P9].

Groumpos PP, Apostolopoulos ID. Modeling the spread of dangerous pandemics with the utilization of a Hybrid Statistical- Advanced-Fuzzy-Cognitive-Map algorithm: the example of COVID-19, Research on Biomedical Engineering. 2021 🔓

[P10].

Apostolopoulos ID, Tzani MA. Industrial object and defect recognition utilizing multilevel feature extraction from industrial scenes with Deep Learning approach, Journal of Ambient Intelligence and Humanized Computing. 2022 🔓

[P11].

Apostolopoulos ID, Papandrianos I, Feleki A, Moustakidis S, Papageorgiou E, Deep learning-enhanced nuclear medicine SPECT imaging applied to cardiac studies: A review, EJNMMI Physics, 2023 🔓

[P12].

Apostolopoulos ID, Papathanasiou ND, Apostolopoulos DJ, Panayiotakis GS. Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review. Eur J Nucl Med Mol Imaging. 2022 🔓

[P13].

Apostolopoulos ID, Apostolopoulos DJ, Papathanasiou ND. Deep Learning Methods to Reveal Important X-ray Features in COVID-19 Detection: Investigation of Explainability and Feature Reproducibility. Reports. 2022 🔓

[P14].

Papandrianos NI, Apostolopoulos ID, Feleki A, Apostolopoulos DJ, Papageorgiou EI. Deep Learning exploration for SPECT MPI polar map images classification in Coronary Artery Disease, Annals of Nuclear Medicine, 2022 🔓

[P15].

Papandrianos NI, Feleki A, Moustakidis S, Papageorgiou E, Apostolopoulos ID, Apostolopoulos DJ, An explainable classification method of SPECT myocardial perfusion images in nuclear cardiology using deep learning and Grad-Cam, Applied Sciences, 2022 🔓

[P16].

Apostolopoulos ID, Papathanasiou ND, Apostolopoulos DJ, A Deep Learning methodology for the detection of abnormal Parathyroid Glands from scintigraphy with 99mTc-sestamibi, Diseases, 2022 🔓

[P17].

Apostolopoulos ID, Papandrianos NI, Papageorgiou EI, Apostolopoulos DJ, Artificial Intelligence Methods for Identifying and Localizing Abnormal Parathyroid Glands: A Review Study, Mach. Learn. Knowl. Extr., 2022 🔓

[P18].

Apostolopoulos ID, Papathanasiou ND, Papandrianos NI, Papageorgiou EI, Panayiotakis GS, Deep Learning assessment for mining important medical image features of various modalities, Diagnostics, 2022 🔓

[P19].

Papandrianos NI, Apostolopoulos ID, Feleki A, Moustakidis S, Kokkinos K, Papageorgiou EI, AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: A review, Nuclear Medicine Communications, 2022 🔓

[P20].

Apostolopoulos DJ, Apostolopoulos ID, Papathanasiou ND, Spyridonidis T, Panayiotakis GS, Detection and localisation of abnormal parathyroid glands: An explainable Deep Learning approach, Algorithms, 2022 🔓

[P21].

Apostolopoulos ID, Athanasoula I, Tzani M, Groumpos P, An explainable Deep Learning framework for detecting and localizing smoke and fire incidents: evaluation of Grad-CAM++ and LIME, MAKE, 2022 🔓

[P22].

Apostolopoulos ID, Fouskas G, Pandis SN, Field calibration of a low-cost Air Quality monitoring device in a southeastern European site using Machine Learning models, Atmosphere, 2023 🔓

[P23].

Apostolopoulos ID, Groumpos PP, Fuzzy Cognitive Maps: Their Role in Explainable Artificial Intelligence, Applied Sciences, 2023 🔓

[P24].

Apostolopoulos ID, Aznaouridis S, Tzani M, An attention-based Deep Convolutional Neural Network for brain tumour and disorder classification and grading in Magnetic Resonance Imaging, Information, 2023 🔓

[P25].

Samaras AD, Moustakidis S, Apostolopoulos ID, Papandrianos NI, Papageorgiou EI, Classification Models for Assessing Coronary Artery Disease Instances Using Clinical and Biometric Data: An explainable man-in-the-loop approach, Scientific Reports, 2023 🔓

[P26].

Samaras AD, Moustakidis S, Apostolopoulos ID, Papandrianos NI, Papageorgiou EI, Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models, Applied Sciences, 2023 🔓

[P27].

Apostolopoulos ID, Papathanasiou ND, Papandrianos NI, Papageorgiou EI, Apostolopoulos DJ, Innovative attention-based explainable feature-fusion VGG19 network for characterising Myocardial Perfusion Imaging SPECT Polar Maps in patients with suspected Coronary Artery Disease, Applied Sciences, 2023 🔓

[P28].

Apostolopoulos DJ, Apostolopoulos ID, Papathanasiou ND, Spyridonidis T, Panayiotakis GS, Explainable Artificial Intelligence Method (ParaNet+) localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism, Algorithms, 2023 🔓

[P29].

Apostolopoulos ID, Aznaouridis S, Tzani M, A General Machine Learning Model for Assessing Fruit Quality Using Deep Image Features, AI, 2023 🔓

[P30].

Feleki A, Apostolopoulos ID, Moustakidis S, Papageorgiou E, Papathanasiou N, Apostolopoulos D, Papandrianos N, Explainable DeepFCM Diagnosis of Coronary Artery Disease: Integrating MPI Imaging, Clinical Data, and Natural Language Insights, Applied Sciences, 2023, 🔓

[P31].

Siouti E, Skyllakou K, Kioutsioukis I, Patoulias D, Apostolopoulos ID, Fouskas G, Pandis SN, Prediction of the concentration and source contributions of PM2.5 and gas-phase pollutants in an urban area with the SmartAQ forecasting system, Atmosphere, 2023, 🔓

[P32].

Apostolopoulos ID, Papandrianos N, Papathanasiou N, Papageorgiou E, Fuzzy Cognitive Map applications in medicine over the last two decades: A review study, Bioengineering, 2024, 🔓

[P33].

Apostolopoulos ID, Papathanasiou ND, Apostolopoulos DJ, Papandrianos N, Papageorgiou EI, Integrating Machine Learning in Clinical Practice for Characterizing the Malignancy of Solitary Pulmonary Nodules in PET/CT Screening, Diseases, 2024, 🔓

[P34].

Apostolopoulos ID, Androulakis S, Kalkavouras P, Fouskas G, Pandis SN, Calibration and inter-unit consistency assessment of an electrochemical sensor system using machine learning, Sensors, 2024, 🔓

CONFERENCE PROCEEDINGS

[C 1]

Apostolopoulos ID et al., A Medical Decision Support System for the Prediction of the Coronary Artery Disease Using Fuzzy Cognitive Maps. In: Kravets A, Shcherbakov M, Kultsova M, Groumpos P, editors. Creativity in Intelligent Technologies and Data Science [Internet]. Cham: Springer International Publishing; 2017 [cited 2020 Jul 7]. p. 269–83. (Communications in Computer and Information Science; vol. 754). 🔓

@ Creativity in Intelligent Technologies and Data Science, Volgograd, Russia, 12 - 17 Sep 2017. Conference Proceeding (view the proceedings)

[C 2]

Apostolopoulos ID, Fouskas G, Pandis S, An IoT integrated Air Quality Monitoring device based on microcomputer technology and leading industry low-cost sensor solutions, Future Access Enablers for Ubiquitous and Intelligent Infrastructures. FABULOUS 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer, Cham 🔓

@ 6th EAI International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures, Zagreb, Croatia, 4-6 May 2022

[C 3]

Apostolopoulos ID, Tzani B, Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic, 🔓

@ The Thirteen IEEE International Conference on Information, Intelligence, Systems and Applications, Corfu, Greece, 18-20 July 2022

[C 4]

Apostolopoulos ID et al., Solitary Pulmonary Nodule malignancy classification utilising 3D features and semi-supervised Deep Learning 🔓

@The Thirteen IEEE International Conference on Information, Intelligence, Systems and Applications, Corfu, Greece, 18-20 July 2022

[C 5]

Apostolopoulos ID et al., Deep learning for the detection and localization of abnormal parathyroid glands in patients with hyperparathyroidism 🔓 (presentation video)

@ 1st Panhellenic Conference of Medical Physics, Athens, Greece, 23-25 Sep 2022

[C 6]

Georgiou M et al., Intelligent Modeling for the food chain using Fuzzy Cognitive Maps 🔓

@ UBT INTERNATIONAL CONFERENCE 2022: RESILIENCE, INNOVATION, AND SUSTAINABILITY Pristina, Kosovo, 29-30 Oct 2022

[C 7]

Athanasoula I et al., Fuzzy Cognitive Maps and Explainable Artificial Intelligence: a critical perspective 🔓

@ UBT INTERNATIONAL CONFERENCE 2022: RESILIENCE, INNOVATION, AND SUSTAINABILITY Pristina, Kosovo, 29-30 Oct 2022

[C 8]

Athanasoula I et al., Evaluation of Grad-CAM for explaining Deep Learning's decisions on various medical imaging datasets 🔓

@ UBT INTERNATIONAL CONFERENCE 2022: RESILIENCE, INNOVATION, AND SUSTAINABILITY Pristina, Kosovo, 29-30 Oct 2022

[C 9]

Apostolopoulos ID et al., Explainable Deep Learning for localising abnormal Parathyroid Glands in parathyroid scintigraphy 🔓

@ Emerging Tech Conference (ETCEI 2022): Edge Intelligence 2022, Patras, Greece, 26-27 Oct 2022

[C 10]

Apostolopoulos ID et al., Diagnosis of Coronary Artery Disease from Myocardial Perfusion Imaging Polar Maps with an innovative attention-based feature-fusion network 🔓 (accepted)

@ 19th International Conference on Machine Learning and Data Mining MLDM 2023, July 15-19, 2023, New York, USA

[C 11]

Feleki A et al., A Fuzzy Cognitive Map learning approach for coronary artery disease diagnosis in Nuclear Medicine 🔓

@ EUSFLAT: 13th Conference of the European Society for Fuzzy Logic and Technology jointly with the AGOP and FQAS conferences, Sep 4-8, 2023, Palma, Spain

[C 12]

Feleki A et al., Deep Fuzzy Cognitive Map methodology for Non-Small Cell Lung Cancer diagnosis based on Positron Emission Tomography imaging,

@The Fourteenth IEEE International Conference on Information, Intelligence, Systems and Applications, University of Thessaly, Volos, Greece, 10-12 July 2023 🔓

[C 13]

Apostolopoulos ID et al., Abnormal Parathyroid Gland localization in scintigraphic images using a Vision Transformer network.

@The Fourteenth IEEE International Conference on Information, Intelligence, Systems and Applications, University of Thessaly, Volos, Greece, 10-12 July 2023 🔓

[C 14]

Samaras AD et al., Explainable Classification for Non-Small Cell Lung Cancer based on Positron Emission Tomography features and clinical data,

@The Fourteenth IEEE International Conference on Information, Intelligence, Systems and Applications, University of Thessaly, Volos, Greece, 10-12 July 2023 🔓

[C 15]

Apostolopoulos ID et al., 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

@The Fifteenth IEEE International Conference on Information, Intelligence, Systems and Applications, Grand Arsenal, Chania, Greece, 16-19 July 2024

[C 16]

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

@The Fifteenth IEEE International Conference on Information, Intelligence, Systems and Applications, Grand Arsenal, Chania, Greece, 16-19 July 2024

IOANNIS (JOHN) D. APOSTOLOPOULOS

PUBLICATIONS

PEER-REVIEWED SCIENTIFIC JOURNALS

CONFERENCE PROCEEDINGS