Abstract
To keep away from irreversible joint damage and systemic issues, knee septic arthritis, a important joint contamination, desires to be recognized rapid and accurately. Traditional analysis techniques that rely on laboratory consequences and medical assessment can be hard and reason healing delays. In order to pick out and categorize knee septic arthritis, this take a look at indicates an AI-based completely diagnostic framework that makes use of X-ray imaging and deep reading fashions, which include CNet, GNet, TabNet, ResNet18, DenseNet and EfficientNetV2B0. The era uses modern day image characteristic extraction strategies to boom precision and dependability, giving scientific specialists a useful tool for choice-making. High diagnostic overall performance is confirmed within the experimental assessment, underscoring the usefulness of the advised method for scientific treatment making plans and early identification.
| Original language | English |
|---|---|
| Title of host publication | International Conference on Sustainable Communication Networks and Application |
| Publisher | IEEE |
| Publication status | Accepted/In press - 6 Oct 2025 |
| Event | International Conference on Sustainable Communication Networks and Application 2025 - Bharath Niketan Engineering College, Theni, India Duration: 15 Oct 2025 → 17 Oct 2025 https://icoscn.com/2025/#:~:text=This%20International%20Conference%20on%20Sustainable%20Communication%20Networks%20and,computing%20architectures%20and%20sustainable%20network%20resource%20management%20frameworks. |
Conference
| Conference | International Conference on Sustainable Communication Networks and Application 2025 |
|---|---|
| Abbreviated title | ICSCN 2025 |
| Country/Territory | India |
| City | Theni |
| Period | 15/10/25 → 17/10/25 |
| Internet address |
Keywords
- deep learning
- artificial intelligence
- Xray images
- multi classification