CORONARY ARTERY DISEASE DIAGNOSIS USING MYOCARDIAL PERFUSION IMAGING POLAR MAPS AND DEEP LEARNING METHODS
Forecasting PM2.5 and NO2 Concentrations in Patras Using Low-Cost Sensors and Machine Learning Abstract: We present a machine learning methodology for forecasting next day’s PM2.5 and NO2 concentrations in Patras, Greece,…
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 Abstract Early detection of Coronary Artery Disease (CAD) and Non-Small Cell Lung Cancer (NSCLC) is crucial for improving…
Abnormal Parathyroid Gland localization in scintigraphic images using a Vision Transformer network Abstract This study proposes a ViT network for classification and localization to aid in detecting abnormal PGs in…
Deep Fuzzy Cognitive Map methodology for Non-Small Cell Lung Cancer diagnosis based on Positron Emission Tomography imaging Abstract Non-Small Cell Lung Cancer (NSCLC) constitutes the major cause of cancer deaths worldwide in both men and…
Diagnosis of Coronary Artery Disease from Myocardial Perfusion Imaging Polar Maps with an innovative attention-based feature-fusion network
Solitary Pulmonary Nodule malignancy classification utilising 3D features and semi-supervised Deep Learning Abstract The volumetric representation of Solitary Pulmonary Nodules (SPN) in Computed Tomography (CT) imaging is mandatory, especially for…
Deep learning for the detection and localization of abnormal parathyroid glands in patients with hyperparathyroidism Abstract Background: Preoperative imaging methods for the localization of abnormal parathyroid glands are widely used to facilitate ensuing…
Evaluation of Grad-CAM for explaining Deep Learning’s decisions on various medical imaging datasets Abstract Deep Learning (DL) is a well-established pipeline for feature extraction in medical and non-medical imaging tasks, such…
Explainable Deep Learning for localising abnormal Parathyroid Glands in parathyroid scintigraphy Abstract Parathyroid scintigraphy with 99mTc-sestamibi (MIBI) is an established technique for localising abnormal Parathyroid Glands (PGs). However, the…
Explainable YOLOv8 model for Solitary Pulmonary Nodules Classification using Positron Emission Tomography and Computed Tomography Scans
The Role of Artificial Intelligence in the Diagnosis, Segmentation, and Prediction of Retinal Vein Occlusion: A Systematic Review Abstract Retinal vein occlusion (RVO) is the second most common cause of vision loss after diabetic retinopathy. It…
Artificial Intelligence Algorithms for Epiretinal Membrane Detection, Segmentation and Postoperative BCVA Prediction: A Systematic Review and Meta-Analysis Epiretinal membrane (ERM) is a common retinal pathology associated with progressive visual impairment, requiring timely and accurate assessment.…
A Review on SPECT Myocardial Perfusion Imaging Attenuation Correction using Deep Learning Abstract Attenuation correction (AC) is an essential process in Single Photon Emission Computed Tomography (SPECT) myocardial perfusion imaging…
A Multi-modal Machine Learning methodology for predicting Solitary Pulmonary Nodule malignancy in patients undergoing PET CT examination
Explainable deep fuzzy cognitive map diagnosis of coronary artery disease: Integrating myocardial perfusion imaging, clinical data, and natural language insights
Integrating Machine Learning in Clinical Practice for Characterizing the Malignancy of Solitary Pulmonary Nodules in PET CT Screening
Innovative attention-based explainable feature-fusion VGG19 network for characterising Myocardial Perfusion Imaging SPECT Polar Maps in patients with suspected Coronary Artery Disease
Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism
An attention-based Deep Convolutional Neural Network for brain tumour and disorder classification and grading in Magnetic Resonance Imaging
An explainable Deep Learning framework for detecting and localising smoke and fire incidents: evaluation of Grad-CAM++ and LIME
AI-based classification algorithms in SPECT myocardial perfusion imaging for cardiovascular diagnosis: A review
Artificial Intelligence methods for identifying and localizing abnormal parathyroid glands: A review study
A Deep Learning methodology for the detection of abnormal Parathyroid Glands from scintigraphy with 99mTc-sestamibi
Applications of Generative Adversarial Networks (GANs) in Positron Emission Tomography (PET) imaging: A review
Deep Learning methods to reveal important X-Ray features in COVID-19 detection: investigation of explainability and fea-ture reproducibility
An explainable classification method of SPECT myocardial perfusion images in nuclear cardiology using deep learning and Grad-Cam
Industrial object and defect recognition utilizing multilevel feature extraction from industrial scenes with Deep Learning approach
Classification of Lung Nodule Malignancy in Computed Tomography Imaging utilising Generative Adversarial Networks and Semi-supervised Transfer Learning
Automatic Classification of Solitary Pulmonary Nodules in PET CT imaging employing Transfer Learning techniques
Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation
Multi-Input Deep Learning Approach for Cardiovascular Disease Diagnosis using Myocardial Perfusion Imaging and Clinical Data
Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks
Extracting Possibly Representative COVID-19 Biomarkers from X-ray Images with Deep Learning Approach and Image Data Related to Pulmonary Diseases
