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Pneumonia

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Diagnostic Value of Deep Learning-Based CT Feature for Severe Pulmonary Infection.

Journal of healthcare engineering
The study aimed to explore the diagnostic value of computed tomography (CT) images based on cavity convolution U-Net algorithm for patients with severe pulmonary infection. A new lung CT image segmentation algorithm (U-Net+ deep convolution (DC)) was...

DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The global pandemic of coronavirus disease 2019 (COVID-19) is continuing to have a significant effect on the well-being of the global population, thus increasing the demand for rapid testing, diagnosis, and treatment. As COVID-19 can cause severe pne...

Diagnosis of Pneumonia by Cough Sounds Analyzed with Statistical Features and AI.

Sensors (Basel, Switzerland)
Pneumonia is a serious disease often accompanied by complications, sometimes leading to death. Unfortunately, diagnosis of pneumonia is frequently delayed until physical and radiologic examinations are performed. Diagnosing pneumonia with cough sound...

Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?

Medicina (Kaunas, Lithuania)
: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 ...

Limited generalizability of deep learning algorithm for pediatric pneumonia classification on external data.

Emergency radiology
PURPOSE: (1) Develop a deep learning system (DLS) to identify pneumonia in pediatric chest radiographs, and (2) evaluate its generalizability by comparing its performance on internal versus external test datasets.

Artificial intelligence on COVID-19 pneumonia detection using chest xray images.

PloS one
Recent studies show the potential of artificial intelligence (AI) as a screening tool to detect COVID-19 pneumonia based on chest x-ray (CXR) images. However, issues on the datasets and study designs from medical and technical perspectives, as well a...

Determining Top Fully Connected Layer's Hidden Neuron Count for Transfer Learning, Using Knowledge Distillation: a Case Study on Chest X-Ray Classification of Pneumonia and COVID-19.

Journal of digital imaging
Deep convolutional neural network (CNN)-assisted classification of images is one of the most discussed topics in recent years. Continuously innovation of neural network architectures is making it more correct and efficient every day. But training a n...

CheXED: Comparison of a Deep Learning Model to a Clinical Decision Support System for Pneumonia in the Emergency Department.

Journal of thoracic imaging
PURPOSE: Patients with pneumonia often present to the emergency department (ED) and require prompt diagnosis and treatment. Clinical decision support systems for the diagnosis and management of pneumonia are commonly utilized in EDs to improve patien...

Evaluating Deep Neural Network Architectures with Transfer Learning for Pneumonitis Diagnosis.

Computational and mathematical methods in medicine
Pneumonitis is an infectious disease that causes the inflammation of the air sac. It can be life-threatening to the very young and elderly. Detection of pneumonitis from X-ray images is a significant challenge. Early detection and assistance with dia...

DR-MIL: deep represented multiple instance learning distinguishes COVID-19 from community-acquired pneumonia in CT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Given that the novel coronavirus disease 2019 (COVID-19) has become a pandemic, a method to accurately distinguish COVID-19 from community-acquired pneumonia (CAP) is urgently needed. However, the spatial uncertainty and mor...