Integrated ensemble CNN and explainable AI for COVID-19 diagnosis from CT scan and X-ray images
In light of the ongoing battle against COVID-19, while the pandemic may eventually subside,
sporadic cases may still emerge, underscoring the need for accurate detection from …
sporadic cases may still emerge, underscoring the need for accurate detection from …
PulmonNet V1: leveraging the benefit of Leaky ReLU activation for the local and multi-scale global feature integration of chest radiographs to classify pulmonary …
Respiratory ailments are conditions that hinder the efficient functioning of the respiratory
system and are a prominent cause of mortality globally with potential triggers including …
system and are a prominent cause of mortality globally with potential triggers including …
Deep learning for lung disease classification using transfer learning and a customized cnn architecture with attention
Many people die from lung-related diseases every year. X-ray is an effective way to test if
one is diagnosed with a lung-related disease or not. This study concentrates on categorizing …
one is diagnosed with a lung-related disease or not. This study concentrates on categorizing …
Classification of Lung Disease in X-Ray Images Using Gray Level Co-Occurrence Matrix Method and Convolutional Neural Network
The lungs are a very important part of the human body, as they serve as a place for oxygen
exchange. They have a very complex task and are susceptible to damage from the polluted …
exchange. They have a very complex task and are susceptible to damage from the polluted …
Computational Thinking in Science Laboratories Based on the Flipped Classroom Model: Computational Thinking, Laboratory Entrepreneurial and Attitude
U Sari, A Ulusoy, HM Pektaş - Journal of Science Education and …, 2025 - Springer
Computational thinking (CT) has gained more value for individuals in a world reshaped by
digital transformation in the last decade. Therefore, educators and researchers are trying to …
digital transformation in the last decade. Therefore, educators and researchers are trying to …
[HTML][HTML] Analyzing the Impact of Data Augmentation on the Explainability of Deep Learning-Based Medical Image Classification
Deep learning models are widely used for medical image analysis and require large
datasets, while sufficient high-quality medical data for training are scarce. Data …
datasets, while sufficient high-quality medical data for training are scarce. Data …
[HTML][HTML] Hybrid AI-Powered Real-Time Distributed Denial of Service Detection and Traffic Monitoring for Software-Defined-Based Vehicular Ad Hoc Networks: A New …
Vehicular Ad Hoc Networks (VANETs) are wireless networks that improve traffic efficiency,
safety, and comfort for smart vehicle users. However, with the rise of smart and electric …
safety, and comfort for smart vehicle users. However, with the rise of smart and electric …
[PDF][PDF] Evaluating the Impact of Data Augmentation on Explainable AI in Medical Image Analysis
FX Liu - 2024 - pure.tue.nl
Deep learning models are widely used in medical image analysis. Data augmentation
methods are introduced to improve the performance of these models. However, lack of …
methods are introduced to improve the performance of these models. However, lack of …
Raspberry Pi Powered Deep Learning-based Chest X-ray Analysis for Medical Diagnosis
Despite the impressive performance, traditional medical imaging analysis equipment is often
costly and cumbersome, limiting accessibility, especially in remote or resource-constrained …
costly and cumbersome, limiting accessibility, especially in remote or resource-constrained …
Intrathoracic Ewing's sarcoma in an adult masquerading as lung abscess
R Lahiri, SS Rawat, K Srikant, S Rao - BMJ Case Reports CP, 2024 - casereports.bmj.com
Intrathoracic extraskeletal Ewing's sarcoma (EES) is a relatively uncommon malignant
tumour. Here, we present a scenario involving an adult man in his 20s with a large …
tumour. Here, we present a scenario involving an adult man in his 20s with a large …