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Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Chest x-ray images for lung disease detection using deep learning techniques: a comprehensive survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
[HTML][HTML] Empowering covid-19 detection: Optimizing performance through fine-tuned efficientnet deep learning architecture
The worldwide COVID-19 pandemic has profoundly influenced the health and everyday
experiences of individuals across the planet. It is a highly contagious respiratory disease …
experiences of individuals across the planet. It is a highly contagious respiratory disease …
Efficient pneumonia detection using Vision Transformers on chest X-rays
Pneumonia is a widespread and acute respiratory infection that impacts people of all ages.
Early detection and treatment of pneumonia are essential for avoiding complications and …
Early detection and treatment of pneumonia are essential for avoiding complications and …
Detection of bruises on red apples using deep learning models
The detection and sorting of bruised apples after harvest play a crucial role in improving
their economic value by eliminating surface defects. This also reduces the risk of …
their economic value by eliminating surface defects. This also reduces the risk of …
Multi-modal deep learning methods for classification of chest diseases using different medical imaging and cough sounds
Chest disease refers to a wide range of conditions affecting the lungs, such as COVID-19,
lung cancer (LC), consolidation lung (COL), and many more. When diagnosing chest …
lung cancer (LC), consolidation lung (COL), and many more. When diagnosing chest …
[HTML][HTML] Ensemble Federated Learning: An approach for collaborative pneumonia diagnosis
Federated learning is a very convenient approach for scenarios where (i) the exchange of
data implies privacy concerns and/or (ii) a quick reaction is needed. In smart healthcare …
data implies privacy concerns and/or (ii) a quick reaction is needed. In smart healthcare …
Role of artificial intelligence in medical image analysis: A review of current trends and future directions
X Li, L Zhang, J Yang, F Teng - Journal of Medical and Biological …, 2024 - Springer
Purpose This review offers insight into AI's current and future contributions to medical image
analysis. The article highlights the challenges associated with manual image interpretation …
analysis. The article highlights the challenges associated with manual image interpretation …
An analysis of deep transfer learning-based approaches for prediction and prognosis of multiple respiratory diseases using pulmonary images
Respiratory diseases can lead to lung failure, which happens when the lungs cannot give
the body enough oxygen. These diseases can be diagnosed using medical data, lung …
the body enough oxygen. These diseases can be diagnosed using medical data, lung …
Emb-trattunet: a novel edge loss function and transformer-CNN architecture for multi-classes pneumonia infection segmentation in low annotation regimes
One of the primary challenges in applying deep learning approaches to medical imaging is
the limited availability of data due to various factors. These factors include concerns about …
the limited availability of data due to various factors. These factors include concerns about …