Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images
importance 8/10
partially solved
COVID-19 diagnosis using AI medical imaging stage: research
Problem
Detecting and classifying pneumonia from chest X-ray images with a model that meets all performance metrics.
Why it matters
Pneumonia is a leading cause of death among children and the elderly worldwide.
What the AI did
Four deep learning models (two pretrained, one CNN, one LSTM) were developed and compared for pneumonia detection from chest X-ray images.
Results
Accuracy 99.22%, precision 99.43%, F1 99.44%, recall 99.4% (abstract truncated)
Impact
Reports high classification metrics on X-ray data; no clinical deployment or validation stated.
Record
| Venue | Diagnostics |
|---|---|
| Published | 2020 |
| Work type | article |
| Authors | Nada M. Elshennawy, Dina M. Ibrahim |
| Citations | 203 (OpenAlex, at import time) |
| References | 36 |
| Model or method | ResNet152V2, MobileNetV2, CNN, LSTM |
| Organization | not stated in source |
| Primary source | https://doi.org/10.3390/diagnostics10090649 |
| Open access | gold |
| Keywords | pneumonia, chest X-ray, deep learning, CNN, image classification |
Importance rating
8
major — millions of lives, an industry or a field
Abstract states pneumonia is one of the main reasons for death among children and the elderly worldwide, matching the major-impact tier; solution is a classification model without clinical validation.