دورية أكاديمية
Radiographic chest wall abnormalities in primary spontaneous pneumothorax identified by artificial intelligence
| العنوان: | Radiographic chest wall abnormalities in primary spontaneous pneumothorax identified by artificial intelligence |
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| المؤلفون: | Ming-Chuan Chiu, Stella Chin-Shaw Tsai, Zhe-Rui Bai, Abraham Lin, Chi-Chang Chang, Guo-Zhi Wang, Frank Cheau-Feng Lin |
| المصدر: | Heliyon, Vol 10, Iss 9, Pp e30023- (2024) |
| بيانات النشر: | Elsevier, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Science (General) LCC:Social sciences (General) |
| مصطلحات موضوعية: | Artificial intelligence, Chest wall, Convolutional neural network, Heatmap, Primary spontaneous pneumothorax, Scale-invariant feature transform, Science (General), Q1-390, Social sciences (General), H1-99 |
| الوصف: | Primary spontaneous pneumothorax (PSP) primarily affects slim and tall young males. Exploring the etiological link between chest wall structural characteristics and PSP is crucial for advancing treatment methods. In this case-control study, chest computed tomography (CT) images from patients undergoing thoracic surgery, with or without PSP, were analyzed using Artificial Intelligence. Convolutional Neural Network (CNN) model of EfficientNetB3 and InceptionV3 were used with transfer learning on the Imagenet to compare the images of both groups. A heatmap was created on the chest CT scans to enhance interoperability, and the scale-invariant feature transform (SIFT) was adopted to further compare the image level. A total of 2,312 CT images of 26 non-PSP patients and 1,122 CT images of 26 PSP patients were selected. Chest-wall apex pit (CAP) was found in 25 PSP and three non-PSP patients (p |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2405-8440 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2405844024060547; https://doaj.org/toc/2405-8440 |
| DOI: | 10.1016/j.heliyon.2024.e30023 |
| URL الوصول: | https://doaj.org/article/9b407f3256cf42ee879788fb0f6325c5 |
| رقم الأكسشن: | edsdoj.9b407f3256cf42ee879788fb0f6325c5 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 24058440 |
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| DOI: | 10.1016/j.heliyon.2024.e30023 |