Pneumonia Detection
18 papers with code • 2 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Pneumonia Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
ChestX-ray14
Most implemented papers
The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-rays
rkharkness/open-data-study
•
•
Model performance results have been exceptional when training and testing on open-source data, surpassing the reported capabilities of AI in pneumonia-detection prior to the COVID-19 outbreak.
COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural Networks
bcprescott/msds
•
•
The chest radiograph appearance of COVID-19 pneumonia is thought to be nonspecific, having presented a challenge to identify an optimal architecture of a convolutional neural network (CNN) that would classify with a high sensitivity among the pulmonary inflammation features of COVID-19 and non-COVID-19 types of pneumonia.
Image quality assessment for machine learning tasks using meta-reinforcement learning
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability.
Making the Most of Text Semantics to Improve Biomedical Vision--Language Processing
microsoft/hi-ml
•
•
We release a new dataset with locally-aligned phrase grounding annotations by radiologists to facilitate the study of complex semantic modelling in biomedical vision--language processing.
Supervised Dictionary Learning with Auxiliary Covariates
Supervised dictionary learning (SDL) is a classical machine learning method that simultaneously seeks feature extraction and classification tasks, which are not necessarily a priori aligned objectives.
An Adaptive and Altruistic PSO-based Deep Feature Selection Method for Pneumonia Detection from Chest X-Rays
rishavpramanik/aapso
•
•
Applied Soft Computing 2022
The proposed method successfully eliminates non-informative features obtained from the ResNet50 model, thereby improving the Pneumonia detection ability of the overall framework.
Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning
In this work, we pre-train DNNs on ultrasound (US) domains instead of ImageNet to reduce the domain gap in medical US applications.
Optimized Deep Feature Selection for Pneumonia Detection: A Novel RegNet and XOR-Based PSO Approach
In this research, an XOR based Particle Swarm Optimization (PSO) is proposed to select deep features from the second last layer of a RegNet model, aiming to improve the accuracy of the CNN model on Pneumonia detection.
