SOTAVerified

Pneumonia Detection

Papers

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Showing 1–50 of 63 papers

TitleStatusHype
Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized DataCode1
Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer ApproachCode1
BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairsCode1
Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive LearningCode1
CovXNet: A multi-dilation convolutional neural network for automatic COVID-19 and other pneumonia detection from chest X-ray images with transferable multi-receptive feature optimizationCode1
COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep LearningCode1
Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray ImagesCode1
Deep Learning for Automatic Pneumonia DetectionCode1
MUXConv: Information Multiplexing in Convolutional Neural NetworksCode1
Multi-Objective Evolutionary Design of Deep Convolutional Neural Networks for Image ClassificationCode1
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep LearningCode1
AI-Enhanced Pediatric Pneumonia Detection: A CNN-Based Approach Using Data Augmentation and Generative Adversarial Networks (GANs)Code0
Comparative Analysis of Vision Transformers and Traditional Deep Learning Approaches for Automated Pneumonia Detection in Chest X-Rays—0
FOAM: A General Frequency-Optimized Anti-Overlapping Framework for Overlapping Object Perception—0
Diagnostic Uncertainty in Pneumonia Detection using CNN MobileNetV2 and CNN from Scratch—0
Novel Pooling-based VGG-Lite for Pneumonia and Covid-19 Detection from Imbalanced Chest X-Ray Datasets—0
FMT:A Multimodal Pneumonia Detection Model Based on Stacking MOE Framework—0
Lightweight Weighted Average Ensemble Model for Pneumonia Detection in Chest X-Ray Images—0
An Explainable Contrastive-based Dilated Convolutional Network with Transformer for Pediatric Pneumonia Detection—0
AutoEncoder Convolutional Neural Network for Pneumonia Detection—0
A systematic review: Deep learning-based methods for pneumonia region detection—0
FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-RaysCode0
Improving Pediatric Pneumonia Diagnosis with Adult Chest X-ray Images Utilizing Contrastive Learning and Embedding Similarity—0
A novel method to enhance pneumonia detection via a model-level ensembling of CNN and vision transformer—0
Pneumonia Detection on chest X-ray images Using Ensemble of Deep Convolutional Neural Networks—0
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection—0
Optimized Deep Feature Selection for Pneumonia Detection: A Novel RegNet and XOR-Based PSO ApproachCode0
Revolutionizing Disease Diagnosis: A Microservices-Based Architecture for Privacy-Preserving and Efficient IoT Data Analytics Using Federated Learning—0
Prediction of Pneumonia and COVID-19 Using Deep Neural Networks—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance—0
SPCXR: Self-supervised Pretraining using Chest X-rays Towards a Domain Specific Foundation Model—0
From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning—0
An Adaptive and Altruistic PSO-based Deep Feature Selection Method for Pneumonia Detection from Chest X-RaysCode0
Supervised Dictionary Learning with Auxiliary CovariatesCode0
Calibrating for Class Weights by Modeling Machine Learning—0
Making the Most of Text Semantics to Improve Biomedical Vision--Language ProcessingCode0
Pneumonia Detection in Chest X-Rays using Neural Networks—0
A Novel Mask R-CNN Model to Segment Heterogeneous Brain Tumors through Image Subtraction—0
Image quality assessment for machine learning tasks using meta-reinforcement learningCode0
Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls—0
Dense Pixel-Labeling for Reverse-Transfer and Diagnostic Learning on Lung Ultrasound for COVID-19 and Pneumonia Detection—0
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation—0
COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural NetworksCode0
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
The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-raysCode0
How Transferable Are Self-supervised Features in Medical Image Classification Tasks?—0
A Radiomics-Boosted Deep-Learning Model for COVID-19 and Non-COVID-19 Pneumonia Classification Using Chest X-ray Image—0
Evaluating the Robustness of Self-Supervised Learning in Medical Imaging—0
Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentations—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