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Improving Real-time High-Resolution Estimates of PM2.5 Concentration Fields in Urban Areas by the SmartAQ+ System with Data Fusion and Machine Learning
Atmospheric Environment
10.1016/j.atmosenv.2025.121665
A Review on SPECT Myocardial Perfusion Imaging Attenuation Correction using Deep Learning
Applied Sciences
10.3390/app152011287
Neural-FCM: A Deep Learning Approach for Weight Matrix Optimization in Fuzzy Cognitive Map Classifiers
Applied Intelligence
10.1007/s10489-025-06795-6
2025
Artificial Intelligence Approaches for Geographic Atrophy Segmentation: A Systematic Review and Meta-Analysis
Bioengineering
10.3390/bioengineering12050475
2025
Monitoring of Indoor Air Quality in a Classroom Combining a Low-Cost Sensor System and Machine Learning
Chemosensors
10.3390/chemosensors13040148
A Multi-modal Machine Learning methodology for predicting Solitary Pulmonary Nodule malignancy in patients undergoing PET CT examination
Big Data and Cognitive Computing
10.3390/bdcc8080085
Fuzzy Cognitive Map applications in medicine over the last two decades: A review study
Bioengineering
10.3390/bioengineering11020139
Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models
Applied Sciences
10.3390/app13148120
Classification Models for Assessing Coronary Artery Disease Instances Using Clinical and Biometric Data: A man-in-the-loop approach
Scientific Reports
10.1038/s41598-023-33500-9
Deep learning – enhanced nuclear medicine SPECT imaging applied on cardiac studies: A review
EJNMMI Physics
10.1186/s40658-022-00522-7
Detection and localisation of abnormal parathyroid glands: An explainable Deep Learning approach
Algorithms
10.3390/a15120455
Deep Learning assessment for mining important medical image features of various modalities
Diagnostics
10.3390/diagnostics12102333
AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: A review
Nuclear Medicine Communications
10.1097/MNM.0000000000001634
An explainable classification method of SPECT myocardial perfusion images in nuclear cardiology using deep learning and Grad-Cam
Applied Sciences
10.3390/app12157592
Deep Learning exploration for SPECT MPI polar map images classification in Coronary Artery Disease
Annals of Biomedical Engineering
10.1007/s12149-022-01762-4
Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review
European Journal of Nuclear Medicine and Molecular Imaging
10.1007/s00259-022-05805-w
Industrial object and defect recognition utilizing multilevel feature extraction from industrial scenes with Deep Learning approach
Ambient Intelligence and Humanized Computing
10.1007/s12652-021-03688-7
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
10.1007/s42600-021-00182-z
Classification of Lung Nodule Malignancy in Computed Tomography Imaging utilising Generative Adversarial Networks and Semi-supervised Transfer Learning
Biocybernetics and Biomedical Enginnering
10.1016/j.bbe.2021.08.006
Automatic Classification of Solitary Pulmonary Nodules in PET CT imaging employing Transfer Learning techniques
Medical and Biological Engineering and Computing
10.1007/s11517-021-02378-y
Advanced fuzzy cognitive maps: state space and rule-based methodology for coronary artery disease detection
Biomedical Physics & Engineering Express
10.1088/2057-1976/abfd83
Multi-Input Deep Learning Approach for Cardiovascular Disease Diagnosis using Myocardial Perfusion Imaging and Clinical Data
Physica Medica
10.1016/j.ejmp.2021.04.011
Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation
Hellenic Journal of Nuclear Medicine
10.1967/s002449912101
Non – invasive modelling methodology for the diagnosis of coronary artery disease using fuzzy cognitive maps
Computer Methods in Biomechanics and Biomedical Engineering
10.1080/10255842.2020.1768534
Extracting Possibly Representative COVID-19 Biomarkers from X-ray Images with Deep Learning Approach and Image Data Related to Pulmonary Diseases
Journal of Medical and Biological Engineering
10.1007/s40846-020-00529-4
Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks
Physical and Engineering Sciences in Medicine
10.1007/s13246-020-00865-4
A machine learning approach for determining solitary pulmonary nodule malignancy in patients undergoing PET/CT examination
Multimedia Tools and Applications
10.1007/s11042-025-20737-x
Utility of disease probability scores to guide decision-making during screening for phaeochromocytoma and paraganglioma: a machine learning modelling cross sectional study
eClinicalMedicine part of The LANCET
10.1016/j.eclinm.2025.103181
