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Pneumonia Detection

Papers

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Showing 51–63 of 63 papers

TitleStatusHype
AutoEncoder Convolutional Neural Network for Pneumonia Detection—0
Calibrating for Class Weights by Modeling Machine Learning—0
Comparative Analysis of Vision Transformers and Traditional Deep Learning Approaches for Automated Pneumonia Detection in Chest X-Rays—0
CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Images—0
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset—0
DECAPS: Detail-Oriented Capsule Networks—0
Deep Compressed Pneumonia Detection for Low-Power Embedded Devices—0
Deep Neural Networks for COVID-19 Detection and Diagnosis using Images and Acoustic-based Techniques: A Recent Review—0
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation—0
Dense Pixel-Labeling for Reverse-Transfer and Diagnostic Learning on Lung Ultrasound for COVID-19 and Pneumonia Detection—0
Diagnostic Uncertainty in Pneumonia Detection using CNN MobileNetV2 and CNN from Scratch—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
Evaluating the Robustness of Self-Supervised Learning in Medical Imaging—0
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All datasetsChestX-ray14Chest X-ray imagesCOVID-19 CXR Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NSGANetV1-A3AUROC0.85—Unverified
2NSGANetV1-XAUROC0.85—Unverified
3CheXNetAUROC0.84—Unverified
4MUXNet-mAUROC0.84—Unverified
5AE-CNNAUROC0.82—Unverified
#ModelMetricClaimedVerifiedStatus
1SelfsynthxAccuracy98.72—Unverified
2DINO-CXRAccuracy95.65—Unverified
3MSTPAccuracy92.79—Unverified
#ModelMetricClaimedVerifiedStatus
1COVID-CXNetF-Score0.85—Unverified