AI Medical Compendium Topic:
Lung

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Comparison of deep learning, radiomics and subjective assessment of chest CT findings in SARS-CoV-2 pneumonia.

Clinical imaging
PURPOSE: Comparison of deep learning algorithm, radiomics and subjective assessment of chest CT for predicting outcome (death or recovery) and intensive care unit (ICU) admission in patients with severe acute respiratory syndrome coronavirus 2 (SARS-...

Establish a normal fetal lung gestational age grading model and explore the potential value of deep learning algorithms in fetal lung maturity evaluation.

Chinese medical journal
BACKGROUND: Prenatal evaluation of fetal lung maturity (FLM) is a challenge, and an effective non-invasive method for prenatal assessment of FLM is needed. The study aimed to establish a normal fetal lung gestational age (GA) grading model based on d...

Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
As being radiation-free, portable, and capable of repetitive use, ultrasonography is playing an important role in diagnosing and evaluating the COVID-19 Pneumonia (PN) in this epidemic. By virtue of lung ultrasound scores (LUSS), lung ultrasound (LUS...

scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics.

Nature communications
Single-cell omics is the fastest-growing type of genomics data in the literature and public genomics repositories. Leveraging the growing repository of labeled datasets and transferring labels from existing datasets to newly generated datasets will e...

IBA-U-Net: Attentive BConvLSTM U-Net with Redesigned Inception for medical image segmentation.

Computers in biology and medicine
Accurate segmentation of medical images plays an essential role in their analysis and has a wide range of research and application values in fields of practice such as medical research, disease diagnosis, disease analysis, and auxiliary surgery. In r...

Transfer learning-based approach for detecting COVID-19 ailment in lung CT scan.

Computers in biology and medicine
This research work aims to identify COVID-19 through deep learning models using lung CT-SCAN images. In order to enhance lung CT scan efficiency, a super-residual dense neural network was applied. The experimentation has been carried out using benchm...

Weighing features of lung and heart regions for thoracic disease classification.

BMC medical imaging
BACKGROUND: Chest X-rays are the most commonly available and affordable radiological examination for screening thoracic diseases. According to the domain knowledge of screening chest X-rays, the pathological information usually lay on the lung and he...

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.

PloS one
Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrained environments, and a computer-aided detection system (CAD) that can identify pneumonia on CXR may help the triage of patients in those environment ...

MHSU-Net: A more versatile neural network for medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Medical image segmentation plays an important role in clinic. Recently, with the development of deep learning, many convolutional neural network (CNN)-based medical image segmentation algorithms have been proposed. Among the...

Artificial Neural Network-Based Deep Learning Model for COVID-19 Patient Detection Using X-Ray Chest Images.

Journal of healthcare engineering
The world is experiencing an unprecedented crisis due to the coronavirus disease (COVID-19) outbreak that has affected nearly 216 countries and territories across the globe. Since the pandemic outbreak, there is a growing interest in computational mo...