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ORCIDIoannis D. Apostolopoulos
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2020 – today
- 2024
[j9]Ioannis D. Apostolopoulos
, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou:
A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination. Big Data Cogn. Comput. 8(8): 85 (2024)- [j8]Ioannis D. Apostolopoulos, Silas Androulakis, Panayiotis Kalkavouras, George Fouskas, Spyros N. Pandis:
Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning. Sensors 24(13): 4110 (2024) - [c9]Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos, Nikolaos D. Papandrianos, Elpiniki I. Papageorgiou:
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. IISA 2024: 1-6 - [c8]Agorastos-Dimitrios Samaras, Anna Feleki, Ioannis D. Apostolopoulos, Serafeim P. Moustakidis, Elpiniki Papageorgiou, Konstantinos Kokkinos, Nikolaos I. Papandrianos:
Medical Decision Support System in Nuclear Medicine Diagnosis for Non-Small Cell Lung Cancer and Coronary Artery Disease: A First Stage Prototype. IISA 2024: 1-8 - 2023
- [j7]Dimitris J. Apostolopoulos, Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Trifon Spyridonidis, George S. Panayiotakis:
Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism. Algorithms 16(9): 435 (2023) - [j6]Ioannis D. Apostolopoulos, Sokratis I. Aznaouridis, Mpesi Tzani:
An Attention-Based Deep Convolutional Neural Network for Brain Tumor and Disorder Classification and Grading in Magnetic Resonance Imaging. Inf. 14(3): 174 (2023) - [j5]Ioannis D. Apostolopoulos, Mpesiana Tzani:
Industrial object and defect recognition utilizing multilevel feature extraction from industrial scenes with Deep Learning approach. J. Ambient Intell. Humaniz. Comput. 14(8): 10263-10276 (2023) - [c7]Anna Feleki, Ioannis D. Apostolopoulos, Konstantinos Papageorgiou, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos, Nikolaos I. Papandrianos:
A Fuzzy Cognitive Map Learning Approach for Coronary Artery Disease Diagnosis in Nuclear Medicine. EUSFLAT/AGOP 2023: 14-25 - [c6]Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos:
Abnormal Parathyroid Gland Localization in Scintigraphic Images Using a Vision Transformer Network. IISA 2023: 1-8 - [c5]Anna Feleki, Ioannis D. Apostolopoulos, Elpiniki Papageorgiou, Serafeim P. Moustakidis, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos, Konstantinos Kokkinos, Nikolaos I. Papandrianos:
Deep Fuzzy Cognitive Map methodology for Non-Small Cell Lung Cancer diagnosis based on Positron Emission Tomography imaging. IISA 2023: 1-6 - [c4]Agorastos-Dimitrios Samaras, Ioannis D. Apostolopoulos, Serafeim P. Moustakidis, Elpiniki Papageorgiou, Nikolaos D. Papathanasiou, Dimitris J. Apostolopoulos, Nikolaos I. Papandrianos:
Explainable Classification for Non-Small Cell Lung Cancer Based on Positron Emission Tomography Features and Clinical Data. IISA 2023: 1-8 - [i6]Ioannis D. Apostolopoulos, Mpesi Tzani, Sokratis I. Aznaouridis:
ChatGPT: ascertaining the self-evident. The use of AI in generating human knowledge. CoRR abs/2308.06373 (2023) - 2022
- [j4]Dimitris J. Apostolopoulos, Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Trifon Spyridonidis, George S. Panayiotakis:
Detection and Localisation of Abnormal Parathyroid Glands: An Explainable Deep Learning Approach. Algorithms 15(12): 455 (2022) - [j3]Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Elpiniki I. Papageorgiou, Dimitris J. Apostolopoulos:
Artificial Intelligence Methods for Identifying and Localizing Abnormal Parathyroid Glands: A Review Study. Mach. Learn. Knowl. Extr. 4(4): 814-826 (2022) - [j2]Ioannis D. Apostolopoulos, Ifigeneia Athanasoula, Mpesi Tzani, Peter P. Groumpos:
An Explainable Deep Learning Framework for Detecting and Localising Smoke and Fire Incidents: Evaluation of Grad-CAM++ and LIME. Mach. Learn. Knowl. Extr. 4(4): 1124-1135 (2022) - [c3]Ioannis D. Apostolopoulos, George Fouskas, Spyros N. Pandis:
An IoT Integrated Air Quality Monitoring Device Based on Microcomputer Technology and Leading Industry Low-Cost Sensor Solutions. FABULOUS 2022: 122-140 - [c2]Ioannis D. Apostolopoulos, Dimitris J. Apostolopoulos, George S. Panayiotakis:
Solitary Pulmonary Nodule malignancy classification utilising 3D features and semi-supervised Deep Learning. IISA 2022: 1-6 - [c1]Ioannis D. Apostolopoulos, Besiana A. Tzani:
Towards an Internet of Things application for the prognosis of Coronary Artery Disease using Machine Learning and Fuzzy Logic. IISA 2022: 1-4 - 2021
- [j1]Ioannis D. Apostolopoulos, Emmanuel G. Pintelas, Ioannis E. Livieris, Dimitris J. Apostolopoulos, Nikolaos D. Papathanasiou, Panagiotis E. Pintelas, George S. Panayiotakis:
Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques. Medical Biol. Eng. Comput. 59(6): 1299-1310 (2021) - 2020
- [i5]Ioannis D. Apostolopoulos:
Experimenting with Convolutional Neural Network Architectures for the automatic characterization of Solitary Pulmonary Nodules' malignancy rating. CoRR abs/2003.06801 (2020) - [i4]Ioannis D. Apostolopoulos, Tzani Bessiana:
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks. CoRR abs/2003.11617 (2020) - [i3]Ioannis D. Apostolopoulos, Peter P. Groumpos:
Non-invasive modelling methodology for the diagnosis of Coronary Artery Disease using Fuzzy Cognitive Maps. CoRR abs/2004.02600 (2020) - [i2]Ioannis D. Apostolopoulos, Peter P. Groumpos, Dimitris J. Apostolopoulos:
State Space Advanced Fuzzy Cognitive Map approach for automatic and non Invasive diagnosis of Coronary Artery Disease. CoRR abs/2004.03372 (2020) - [i1]Ioannis D. Apostolopoulos, Mpesiana Tzani:
Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19. CoRR abs/2011.11305 (2020)
Coauthor Index
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