AIMC Topic: Pneumonia
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Classification of COVID-19 from community-acquired pneumonia: Boosting the performance with capsule network and maximum intensity projection image of CT scans.
Computers in biology and medicine
Jan 23, 2023
BACKGROUND: The coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP) present a high degree of similarity in chest computed tomography (CT) images. Therefore, a procedure for accurately and automatically distinguishing between th...
Deep learning for predicting the risk of immune checkpoint inhibitor-related pneumonitis in lung cancer.
Clinical radiology
Jan 14, 2023
AIM: To develop and validate a nomogram model that combines computed tomography (CT)-based radiological factors extracted from deep-learning and clinical factors for the early predictions of immune checkpoint inhibitor-related pneumonitis (ICI-P).
Coronavirus covid-19 detection by means of explainable deep learning.
Scientific reports
Jan 10, 2023
The coronavirus is caused by the infection of the SARS-CoV-2 virus: it represents a complex and new condition, considering that until the end of December 2019 this virus was totally unknown to the international scientific community. The clinical mana...
LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.
Sensors (Basel, Switzerland)
Jan 2, 2023
This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-ray (CXR) images. This framework is termed optimized DenseNet201 for lung diseases (LDDNet). The pro...
AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.
European radiology
Dec 16, 2022
OBJECTIVES: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algori...
Unsupervised landmark detection and classification of lung infection using transporter neural networks.
Computers in biology and medicine
Nov 25, 2022
Supervised deep learning techniques have been very popular in medical imaging for various tasks of classification, segmentation, and object detection. However, they require a large number of labelled data which is expensive and requires many hours of...
Deep Learning Models to Predict Fatal Pneumonia Using Chest X-Ray Images.
Canadian respiratory journal
Nov 24, 2022
BACKGROUND AND AIMS: Chest X-ray (CXR) is indispensable to the assessment of severity, diagnosis, and management of pneumonia. Deep learning is an artificial intelligence (AI) technology that has been applied to the interpretation of medical images. ...
Generative adversarial network based data augmentation for CNN based detection of Covid-19.
Scientific reports
Nov 10, 2022
Covid-19 has been a global concern since 2019, crippling the world economy and health. Biological diagnostic tools have since been developed to identify the virus from bodily fluids and since the virus causes pneumonia, which results in lung inflamma...
Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training.
Mycoses
Oct 31, 2022
BACKGROUND: Currently, the diagnosis of invasive pulmonary aspergillosis (IPA) mainly depends on the integration of clinical, radiological and microbiological data. Artificial intelligence (AI) has shown great advantages in dealing with data-rich bio...
CX-DaGAN: Domain Adaptation for Pneumonia Diagnosis on a Small Chest X-Ray Dataset.
IEEE transactions on medical imaging
Oct 27, 2022
Recent advances in deep learning led to several algorithms for the accurate diagnosis of pneumonia from chest X-rays. However, these models require large training medical datasets, which are sparse, isolated, and generally private. Furthermore, these...
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