Pneumonia Detection

Pneumonia detection research focuses on developing accurate and efficient automated diagnostic tools, primarily using chest X-ray images, to address the significant global health burden of this disease. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), vision transformers, and their ensembles, often incorporating attention mechanisms and transfer learning techniques to improve diagnostic accuracy and efficiency. These advancements aim to improve diagnostic speed and consistency, particularly in resource-limited settings, and contribute to more effective pneumonia management and reduced mortality.

Papers

August 23, 2024

A systematic review: Deep learning-based methods for pneumonia region detection
Xinmei Xu
Deep Learning Deep Learning Model Systematic Review Deep Learning Based Pneumonia Detection

August 8, 2024

Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer Approach
Alireza Saber, Pouria Parhami, Alimohammad Siahkarzadeh, Mansoor Fateh, Amirreza Fateh
High Efficiency ResNet Based Lung Segmentation Transformer Attention Pneumonia Detection Multi Scale Transformer

June 21, 2024

FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-Rays
Ayush Roy, Anurag Bhattacharjee, Diego Oliva, Oscar Ramos-Soto, Francisco J. Alvarez-Padilla, Ram Sarkar
Chest X Ray Chest X Ray Image Attention Based Deep Ventilator Associated Pneumonia Pneumonia Detection

March 31, 2024

Pneumonia App: a mobile application for efficient pediatric pneumonia diagnosis using explainable convolutional neural networks (CNN)
Jiaming Deng, Zhenglin Chen, Minjiang Chen, Lulu Xu, Jiaqi Yang, Zhendong Luo, Peiwu Qin
Neural Network CNN Network Mobile Application Ventilator Associated Pneumonia Pneumonia Detection Lung Nodule Localization Pneumonia Diagnosis

January 4, 2024

A novel method to enhance pneumonia detection via a model-level ensembling of CNN and vision transformer
Sandeep Angara, Nishith Reddy Mannuru, Aashrith Mannuru, Sharath Thirunagaru
Convolutional Neural Network Vision Transformer New Method Model Ensembling Improved Classification Pneumonia Detection Pneumonia Diagnosis

December 13, 2023

Pneumonia Detection on chest X-ray images Using Ensemble of Deep Convolutional Neural Networks
Alhassan Mabrouk, Rebeca P. Díaz Redondo, Abdelghani Dahou, Mohamed Abd Elaziz, Mohammed Kayed
Convolutional Neural Network Deep Convolutional Neural Network Ensemble Learning Diverse Ensemble Chest X Ray Image Convolutional Neural Network Model Pneumonia Detection

August 31, 2023

Optimized Deep Feature Selection for Pneumonia Detection: A Novel RegNet and XOR-Based PSO Approach
Fatemehsadat Ghanadi Ladani, Samaneh Hosseini Semnani
Feature Selection Particle Swarm Optimization Supernet Training Pneumonia Detection

August 27, 2023

Revolutionizing Disease Diagnosis: A Microservices-Based Architecture for Privacy-Preserving and Efficient IoT Data Analytics Using Federated Learning
Safa Ben Atitallah, Maha Driss, Henda Ben Ghezala
Data Analytics Microservice Architecture Pneumonia Detection Learning Based Disease Diagnosis

August 20, 2023

Prediction of Pneumonia and COVID-19 Using Deep Neural Networks
M. S. Haque, M. S. Taluckder, S. B. Shawkat, M. A. Shahriyar, M. A. Sayed, C. Modak
Deep Neural Network Human Prediction Covid 19 Medical Image Analysis Chest X Ray Image Ventilator Associated Pneumonia Pneumonia Detection Pneumonia Diagnosis

May 4, 2023

Forward-Forward Contrastive Learning
Md. Atik Ahamed, Jin Chen, Abdullah-Al-Zubaer Imran
Contrastive Learning Medical Image Classification Chest X Ray Datasets Pneumonia Detection

January 25, 2023

Self-Supervised Curricular Deep Learning for Chest X-Ray Image Classification
Iván de Andrés Tamé, Kirill Sirotkin, Pablo Carballeira, Marcos Escudero-Viñolo
Supervised ImageNet Chest X Ray Curriculum Learning Medical Image Data Pneumonia Detection Supervised Training

January 20, 2023

Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance
Wardah Ali, Eesha Qureshi, Omama Ahmed Farooqi, Rizwan Ahmed Khan
Generative Adversarial Network Class Imbalance Chest X Ray Image Ventilator Associated Pneumonia Pneumonia Detection ChestX Ray8 Dataset

November 23, 2022

SPCXR: Self-supervised Pretraining using Chest X-rays Towards a Domain Specific Foundation Model
Syed Muhammad Anwar, Abhijeet Parida, Sara Atito, Muhammad Awais, Gustavo Nino, Josef Kitler, Marius George Linguraru
Pre Trained Model Chest X Ray Self Supervised Pretraining Lung Segmentation Pneumonia Detection CXR Lt Domain Specific Foundation Model

October 29, 2022

Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images
Shengchao Chen, Sufen Ren, Guanjun Wang, Mengxing Huang, Chenyang Xue
Inherent Interpretability Chest X Ray Chest X Ray Image Ventilator Associated Pneumonia Pneumonia Detection

August 6, 2022

An Adaptive and Altruistic PSO-based Deep Feature Selection Method for Pneumonia Detection from Chest X-Rays
Rishav Pramanik, Sourodip Sarkar, Ram Sarkar
Feature Selection Adaptive Importance Chest X Ray Ventilator Associated Pneumonia Pneumonia Detection Target Dataset

May 10, 2022

Calibrating for Class Weights by Modeling Machine Learning
Andrew Caplin, Daniel Martin, Philip Marx
Machine Learning Class Imbalance Calibration Performance Machine Learning Algorithm Pneumonia Detection Class Weight

April 7, 2022

Pneumonia Detection in Chest X-Rays using Neural Networks
Narayana Darapaneni, Ashish Ranjan, Dany Bright, Devendra Trivedi, Ketul Kumar, Vivek Kumar, Anwesh Reddy Paduri
Neural Network Convolutional Neural Network Chest X Ray Pneumonia Detection

January 25, 2022

Dense Pixel-Labeling for Reverse-Transfer and Diagnostic Learning on Lung Ultrasound for COVID-19 and Pneumonia Detection
Gautam Rajendrakumar Gare, Andrew Schoenling, Vipin Philip, Hai V Tran, Bennett P deBoisblanc, Ricardo Luis Rodriguez, John Michael Galeotti
Segmentation Model Sparse Label Pre Trained Segmentation Model Pneumonia Detection Lung Ultrasound Dense Label Backward Transfer

December 14, 2021

COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural Networks
Julianna Antonchuk, Benjamin Prescott, Philip Melanchthon, Robin Singh
Convolutional Neural Network Covid 19 Radiology Imaging Ventilator Associated Pneumonia Pneumonia Detection Influenza Virus

Pneumonia Detection

Papers

A systematic review: Deep learning-based methods for pneumonia region detection

Efficient and Accurate Pneumonia Detection Using a Novel Multi-Scale Transformer Approach

FA-Net: A Fuzzy Attention-aided Deep Neural Network for Pneumonia Detection in Chest X-Rays

Pneumonia App: a mobile application for efficient pediatric pneumonia diagnosis using explainable convolutional neural networks (CNN)

A novel method to enhance pneumonia detection via a model-level ensembling of CNN and vision transformer

Pneumonia Detection on chest X-ray images Using Ensemble of Deep Convolutional Neural Networks

Optimized Deep Feature Selection for Pneumonia Detection: A Novel RegNet and XOR-Based PSO Approach

Revolutionizing Disease Diagnosis: A Microservices-Based Architecture for Privacy-Preserving and Efficient IoT Data Analytics Using Federated Learning

Prediction of Pneumonia and COVID-19 Using Deep Neural Networks

Forward-Forward Contrastive Learning

Self-Supervised Curricular Deep Learning for Chest X-Ray Image Classification

Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance

SPCXR: Self-supervised Pretraining using Chest X-rays Towards a Domain Specific Foundation Model

Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images

An Adaptive and Altruistic PSO-based Deep Feature Selection Method for Pneumonia Detection from Chest X-Rays

Calibrating for Class Weights by Modeling Machine Learning

Pneumonia Detection in Chest X-Rays using Neural Networks

Dense Pixel-Labeling for Reverse-Transfer and Diagnostic Learning on Lung Ultrasound for COVID-19 and Pneumonia Detection

COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural Networks